Editorial Manager(tm) for PLoS Genetics Manuscript Draft
Manuscript Number: PGENETICS-D-11-00413
Title: Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets
Short Title: Integrative association analysis of gene sets
Article Type: Research Article
Section/Category: Natural Variation
Keywords: gene set analysis; eQTL; integrative genomics
Corresponding Author: Sayan Mukherjee
Corresponding Author's Institution: Duke University
First Author: Qing Xiong
Order of Authors: Qing Xiong;Nicola Ancona;Elizabeth Hauser;Sayan Mukherjee;Terrence Furey
Abstract: Background: Single variant or single gene analyses generally account for only a small proportion of the phenotypic variation in complex traits. Alternatively, gene set or pathway association analyses are playing an increasingly important role in uncovering genetic architectures of complex traits through the identification of systematic genetic interactions. Two dominant paradigms for gene set analyses are association analyses based on SNP genotypes and those based on gene expression profiles. However, gene-disease association can manifest in many ways such as alterations of gene expression, genotype and copy number, thus an integrative approach combining multiple forms of evidence can more accurately and comprehensively capture pathway associations.
Methodology: We have developed a single statistical framework, Gene Set Association Analysis (GSAA), that simultaneously measures genome-wide patterns of genetic variation and gene expression variation to identify sets of genes enriched for differential expression and/or trait-associated genetic markers. Simulation studies illustrate that joint analyses of genomic data increase the power to detect real associations when compared to gene set methods that use only one genomic data type.
Significance/Findings: The analyses of two human disease, glioblastoma and Crohn's disease, detected abnormalities in previously identified disease-associated pathways, such as pathways related to the PI3K signaling, DNA damage response, and activation of NF-κB. In addition, GSAA revealed novel pathway associations, for example differential genetic and expression characteristics in genes from the ABC transporter family in glioblastoma and from the HLA system in Crohn's disease. These demonstrate that GSAA can help uncover biological pathways underlying human diseases and complex traits. Software is freely available at http://gsaa.genome.duke.edu.
Suggested Reviewers: Eleazar Eskin UCLA [email protected]
Eric Stone North Carolina State Unviersity [email protected]
Emmanouil Dermitzakis Wellcome Trust Sanger Institute [email protected]
Vamsi Mootha Harvard University [email protected]
Opposed Reviewers:
Cover Letter
DUKE UNIVERSITY DEPARTMENT OF STATISTICAL SCIENCE D URHAM NC 27708-0251 - USA
SAYAN MUKHERJEE
ASSISTANT PROFESSOR OF STATISTICAL SCIENCE
COMPUTER SCIENCE AND MATHEMATICS INVESTIGATOR
INSTITUTE FOR GENOME Wednesday, February 23, 2011 SCIENCES & POLICY
tel/fax: +1 919 684 4608/8594 [email protected]
Dear Editor:
We are submitting our manuscript entitled "Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets" for your review. Increasing amounts of diverse genome-wide data for complex traits and diseases are available and continue being rapidly generated, but our understanding of these data is not keeping pace. The primary goal of this study is to develop a more effective method to simultaneously leverage information from multiple genomic data, particularly genotype and expression data, to identify biological pathways underlying complex traits and diseases. We believe that this work represents a substantial advance in the joint analysis of genome-wide association data and genome-wide expression data in the context of complex traits and diseases and will be of broad interest to your readership.
Two major approaches to uncover the genetic architecture of traits have been genome-wide association studies (GWAS), to examine correlations between individual genetic variants and trait variation, and gene expression-based studies, to examine correlations between gene expression and trait variation. Despite the enormous success of GWA studies, the identified single nucleotide polymorphisms (SNPs) explain only a small proportion of the phenotypic variation, and the predictive power of these SNPs remains low for many complex diseases. Gene set or pathway- based approaches have shown some success as an alternative to single locus analyses in an attempt to address the limited explanatory power of identified single variants. However, existing approaches have focused on pathway analyses of a single data type, especially genotype data or expression data, and didn’t offer a integrative solution at the pathway level that takes advantage of the complementary information available in different genome-wide data such as genotype and expression information.
Our novel Gene Set Association Analysis (GSAA) method integrates multiple genomic data to better understand the biology of complex traits. GSAA simultaneously considers multiple data types employing a pathway-based approach that has been repeatedly shown to be more robust than single gene analyses and offers an increased interpretability of results. Importantly, GSAA does not require matched samples, meaning expression and genotype data need not be from the same samples. Thus, combinations of existing GWAS and expression data generated from different studies can be readily employed.
We conducted a comprehensive simulation study and show that GSAA has greater power to detect association signals than other methods. We employed GSAA in an analysis ofglioblastoma and Crohn’s disease data to demonstrate its utility in analysis and interpretation. Our results show that GSAA can robustly detect signals found in either data type and better highlights key pathways that show variation at the genotype level as well as the expression level. While we concentrate on gene expression and genotype data, GSAA is easily extensible to accommodate additional data types such as DNA copy number or DNA methylation data. The general framework of GSAA will also allow the incorporation of higher resolution genome sequence data as it becomes available for greater numbers of samples in the future.
In short, we believe our work described in this manuscript provides a critical methodological advance in genome analyses of complex traits and clearly illustrates its utility on data from previous studies of human disease. We believe that GSAA will greatly complement current GWAS analyses and offers an important alternative way in which to comprehensively understand the genetic underpinnings underlying complex traits and diseases. We strongly believe this work will be of great interest to a broad audience and that your journal is the proper venue for its publication.
PLoS Genetics has a number of excellent associate editors on its board. For this particular work, we believe that Vivian Cheung in particular has the most appropriate knowledge and background to accurately evaluate the merits of our submission. If Dr. Cheung is unable to act as the editor, we feel that Leonid Kruglyak and GoncaloAbecasis would also be well qualified.
Please note that we submitted an earlier version of this paper to PLoS Genetics. Greg Gibson was the section editor. We addressed all of the reviewer comments from that submission. This new paper is very different from our previous submission, in part due to all of the changes addressing the reviewer comments. That review and our responses are included in
Yours sincerely,
Sayan Mukherjee, on behalf of the other authors
2 *Manuscript Click here to download Manuscript: gsaa_manuscript.pdf
1 Integrating genetic and gene expression evidence into genome-wide association 2 analysis of gene sets
3 Qing Xiong1, Nicola Ancona2, Elizabeth R. Hauser3, Sayan Mukherjee4,#,*, Terrence S. Furey1,#,*
4 1Department of Genetics, Department of Biology, Lineberger Comprehensive Cancer Center, and 5 Carolina Center for Genomics and Society, The University of North Carolina at Chapel Hill, Chapel Hill, 6 NC 27599, USA;
7 2Institute of Intelligent Systems for Automation National Research Council, Bari IT 70126, Italy;
8 3Center for Human Genetics and Section of Medical Genetics, Department of Medicine, Duke University, 9 Durham, NC 27710, USA;
10 4Departments of Statistical Science, Computer Science, and Mathematics, Institute for Genome Sciences 11 & Policy, Duke University, Durham, NC 27708, USA;
12 #These authors contributed equally to this work
13 *E-mail: [email protected] (SM), [email protected] (TSF)
14
1 15 Abstract 16 17 Single variant or single gene analyses generally account for only a small proportion of the phenotypic 18 variation in complex traits. Alternatively, gene set or pathway association analyses are playing an 19 increasingly important role in uncovering genetic architectures of complex traits through the identification 20 of systematic genetic interactions. Two dominant paradigms for gene set analyses are association analyses 21 based on SNP genotypes and those based on gene expression profiles. However, gene-disease association 22 can manifest in many ways such as alterations of gene expression, genotype and copy number, thus an 23 integrative approach combining multiple forms of evidence can more accurately and comprehensively 24 capture pathway associations. We have developed a single statistical framework, Gene Set Association 25 Analysis (GSAA), that simultaneously measures genome-wide patterns of genetic variation and gene 26 expression variation to identify sets of genes enriched for differential expression and/or trait-associated 27 genetic markers. Simulation studies illustrate that joint analyses of genomic data increase the power to 28 detect real associations when compared to gene set methods that use only one genomic data type. The 29 analyses of two human disease, glioblastoma and Crohn’s disease, detected abnormalities in previously 30 identified disease-associated pathways, such as pathways related to the PI3K signaling, DNA damage 31 response, and activation of NF-κB. In addition, GSAA revealed novel pathway associations, for example 32 differential genetic and expression characteristics in genes from the ABC transporter family in 33 glioblastoma and from the HLA system in Crohn’s disease. These demonstrate that GSAA can help 34 uncover biological pathways underlying human diseases and complex traits. Software is freely available 35 at http://gsaa.genome.duke.edu.
36
2 37
38 Author Summary 39 40 Phenotypic variation observed in complex traits or diseases generally arises from intricate interactions 41 between multiple genes and environmental factors. Rather than treating each gene as a separate unit, gene 42 set analysis extracts information from groups of genes that are biologically related. It is a powerful way to 43 uncover the genetic architectures of complex traits. Within a gene set, both gene expression variation and 44 genotypic variation can contribute to phenotypic variation, therefore the joint analysis of expression data 45 and genotype data can more accurately and comprehensively assess association between a gene set and a 46 phenotype. We developed a novel statistical framework for identifying biological pathways associated 47 with phenotypic variation based on both gene expression information and genotype information. We 48 demonstrated that our method is more powerful than gene set association analyses based on a single data 49 type using extensive simulations. We further validated our method using data from two diseases. Our 50 method successfully identified molecular pathways deregulated in these diseases. Data from genome-wide 51 association studies and gene expression experiments have been growing at an unprecedented rate. Our 52 method will be used to extract biological insights from this ocean of genomic data and will contribute to a 53 better molecular understanding of disease. 54
3 55
56 Introduction
57 Dissecting the genetic and molecular mechanisms underlying complex traits, including many diseases, 58 is one of the key scientific goals in the post-genomic era. In the past decade, genome-wide association 59 studies (GWAS) have emerged as one of the main strategies in finding genetic variants associated with 60 trait variation, and a large number of genetic associations have been identified for a wide variety of 61 common complex diseases as listed in the GWAS catalog [1] (http://www.genome.gov/gwastudies). 62 Despite the enormous success of these GWAS studies in uncovering important genetic effects, the 63 identified single nucleotide polymorphisms (SNPs) explain only a small proportion of the phenotypic 64 variation, and the predictive power of these SNPs remains low for many complex diseases [2].
65 Current GWAS focus on single-SNP analysis to identify causal variants. These analyses have two 66 limitations. First, an initial GWA scan can yield a large number of statistically significant loci associated 67 with a complex disease which may include causal variants, markers in strong linkage disequilibrium (LD) 68 with causal variants, and some spurious associations stemming from population substructure or other 69 sources of error. It is very difficult to distinguish the causal variants because GWAS analyze each locus 70 independently. To minimize false associations, then secondly, GWAS often identify only a few of the 71 most significant SNPs for biological validation, but these SNPs generally only account for a small 72 proportion of the phenotypic variation. However, a common pattern of the allelic architecture of many 73 diseases is the existence of potentially hundreds of susceptibility loci that increase the risk of disease, but 74 only a few variants have large effects and most have small effects that may not be found by association 75 analyses of individual variants [3].
76 To overcome these challenges of current GWAS approaches, gene set/pathway association analyses 77 have been developed that identify variation in pathway activity or function associated with trait variation. 78 Compared to single-gene or single-SNP analyses, set-based approaches can potentially 1) reduce the false 79 positives or decrease the uncertainty around causal genes or variants by inferring associations over sets of 80 biologically related genes; 2) facilitate interpretation of the results by providing insights into the 81 functional links between implicated genes or variants; and 3) uncover a significant biological effect 82 distributed over multiple loci even if changes in any individual locus have a small effect. Arguably, this 83 strategy is better suited to capture the allelic architectures of complex diseases. Two dominant paradigms 84 for gene set analyses are association analyses based on gene expression profiles and those based on SNP 85 genotypes. Numerous expression-based strategies have been developed [4,5,6,7,8,9,10,11,12] and each 86 method has its advantages, limitations, and assumptions (see [13,14,15,16,17] for a review and for 87 comparisons). Fewer methods have been developed for pathway analyses using SNP data 88 [18,19,20,21,22,23,24].
89 Gene set analyses based on a single data type, for example gene expression data or SNP data, have 90 successfully revealed altered cellular processes associated with complex diseases [25,26,27,28]. However, 91 an integrative statistical framework and computational platform for set-based analyses that can 92 simultaneously leverage information across both expression data and SNP data is still lacking. Valuable 93 associations may be discarded in single data type analyses. For instance, genes with only genetic 94 alterations are not considered in gene set analyses based solely on expression data. Similarly, genes with 95 only expression changes cannot be captured by a purely SNP-based approach. This may miss inferences
4 96 of gene-disease association that result, in part, from the complex interplay of genetic alterations and gene 97 expression changes leading to the development and progression of diseases. These issues create a need to 98 integrate both genetic and gene expression evidence into the association analysis of gene sets. The 99 observation that expression quantitative trait loci (eQTLs) or eSNPs were more likely detected as disease 100 variants in association studies than SNPs not associated with expression differences [29,30] is additional 101 evidence supporting the need for methods integrating gene expression analysis and SNP analysis.
102 In this study, we propose a novel integrative method called Gene Set Association Analysis (GSAA) for 103 the joint analysis of gene expression and SNP data using a pathway-based strategy for more accurate and 104 comprehensive inference of associations. GSAA builds a hierarchical model that incorporates multiple 105 levels of analyses into a single statistical framework to analyze genetic variation across all SNPs mapped 106 to genes and expression variation over all genes simultaneously. The model integrates these two types of 107 genomic information as overall evidence for gene set association analysis.
108 Using extensive simulation studies, we illustrated that GSAA substantially outperforms each of three 109 gene set methods that use only one genomic data source, and that joint analyses reduced the false 110 discovery rate (FDR) in all simulated scenarios and increased the power in nearly all simulated scenarios. 111 We further validated the ability of GSAA to identify association signals in human disease using datasets 112 from glioblastoma and Crohn’s disease. We found significant associations of well-known disease- 113 associated pathways, such as pathways related to PI3K signaling and DNA damage response in 114 glioblastoma and pathways involved in the activation of NF-κB in Crohn’s disease. These integrative 115 analyses also revealed novel pathway associations we did not find in single data analyses, for example 116 aberrations in ABC transporter family in glioblastoma and in the human leukocyte antigen (HLA) system 117 in Crohn’s disease.
118 Java-based software implementing GSAA is freely available at http://gsaa.genome.duke.edu. The 119 software includes a user-friendly and straightforward graphical user interface, and provides full support 120 for the visualization of results. In addition, we also provide a separate module called Gene Set 121 Association Analysis-SNP (GSAA-SNP) that was used in this study and performs pathway-based analysis 122 based solely on SNP genotype data.
123 Results
124 We performed an extensive simulation study to illustrate the power of GSAA under various conditions 125 of genetic association and differential expression. This was followed by application of GSAA to analyze 126 Glioblastoma data as well as Crohn’s disease data.
127 A brief summary of the hierarchical model that was implemented via GSAA (see Materials and 128 Methods for details) follows to better explain the results. The model is outlined in Figure 1 with the key 129 steps consisting of 1) gene level scores for differential expression and genetic association respectively 130 (Figure 1, Differential gene expression score, Single-SNP association score/SNP-set association score) 2) 131 a single metric that combines the gene level scores (Figure 1, Gene association score), and 3) the 132 evaluation of these scores in terms of gene sets or pathways (Figure 1, Gene set/pathway association test).
133 Simulation Studies
5 134 We conducted a comprehensive simulation study to illustrate the power of GSAA under various 135 conditions of genetic association and differential expression and to justify the use of certain summary 136 statistics for data integration. These simulations were designed to address two primary questions: 1) what 137 is the relative performance and what are the advantages of the various statistical summaries explored to 138 integrate evidence in our pathway-based approach; 2) can we reduce the FDR and increase the power of 139 association tests by integrating expression and genotypic data into pathway-based analyses.
140 GSAA uses summary statistics to summarize evidence at two distinct steps. The first occurs when 141 evidence of differential expression is combined with evidence of genetic association at the level of single 142 genes (Figure 1, Gene association score). The second is when this single gene evidence is aggregated 143 across genes within an a priori defined gene set (Figure 1, Gene set/pathway association test). To 144 combine expression and association evidence at the gene level, we evaluated the following statistics (see 145 Materials and Methods for details): a z-score based sum statistic (zs), a statistic based on Fisher’s method 146 (fm), and a rank sum statistic (rs). To integrate evidence across genes we used a weighted Kolmogorov- 147 Smirnov (K-S) statistic (ks). This results in variations of GSAA indexed by these two choices, for 148 example GSAAzs-ks uses the z-score based sum statistic at the gene level and the weighted K-S statistic 149 at the gene set level. The variations of GSAA we compared were zs-ks, fm-ks, and rs-ks. We added to 150 these comparisons a SNP based gene set association analysis called GSAA-SNP (see Materials and 151 Methods), the previously developed Gene Set Enrichment Analysis (GSEA) [4] that performs expression 152 based enrichment analysis, and a variant of GSEA we implemented that ranks genes based on the absolute 153 value of their expression differences that we refer to as GSEAndes (see Materials and Methods).
154 We designed five scenarios in our simulation study to test how each of the methods evaluated 155 performed under varying magnitudes and presence of signals in the SNP and expression data with respect 156 to case versus control samples. In each scenario, we simulated genotype and expression data for 1000 157 genes. Only one of 100 defined genes sets contained causal genes. This “casual gene set” contained 158 sixteen genes of which a subset were genetically associated and differentially expressed. The remaining 159 99 gene sets corresponded to a null model and were composed of a random subset of the remaining 984 160 non-casual genes. Note that a non-casual gene may be assigned to multiple gene sets by this design (see 161 Materials and Methods for details). The five scenarios are distinguished by the degree and type of signal 162 embedded in the genes constituting the causal gene set:
163 S1: Eight of the sixteen genes are both genetically associated with the phenotype and differentially 164 expressed with these eight genes up-regulated in cases;
165 S2: Four genes are both genetically associated and differentially expressed, all up-regulated in the cases. 166 Four other genes are only differentially expressed, all up-regulated in cases;
167 S3: Four genes are both genetically associated and differentially expressed, all up-regulated in cases. Four 168 other genes are only genetically associated;
169 S4: Eight of the genes are both genetically associated with the phenotype and differentially expressed, six 170 of them up-regulated in cases and the other two down-regulated in cases;
171 S5: Four genes are only up-regulated in cases. Four other genes are only genetically associated.
172 In each scenario, the strength of association at the causal loci in the SNP data is determined by the odds
6 173 ratios at the loci where the odds ratio is drawn independently from a uniform distribution (see Materials 174 and Methods). The extent of differential expression is determined by the effect size at each gene in a 175 regression model with the effect size drawn independently from a uniform distribution (see Materials and 176 Methods). This process allows for the modeling of a spectrum of effect sizes at the causal loci as well as 177 of the differentially expressed genes. 178 179 As stated above, the two objectives of the simulation study were first to select the summary statistic to 180 use for integration across genomic data sources at the single-gene level, and second to quantitate the 181 benefit of an integrative model. Results using the simulated data described above for GSAA and for the 182 three single data type analyses, GSAA-SNP, GSEA, and GSEAndes, are reported in Table 1. For these 183 results, the odds ratio for simulating the genetic association was drawn from a uniform distribution (U 184 [1.1, 1.3]). Results using U [1.2, 1.4] are shown in Table S1. The average p-value, FDR and FWER for 185 the causal gene set over 200 replicates and the power of each method in each scenario are reported. The p- 186 value, FDR and FWER were calculated based on 2000 permutations of phenotype labels. Power was 187 calculated as the proportion of replicates for which the p-value for the causal gene set was less than 0.05. 188 189 With respect to our first objective, these results show that for combining information at the single gene 190 level, the z-score based sum statistic performs substantially better than the other two statistics with respect 191 to the FDR or FWER (Table 1, Table S1). Interestingly, the rank sum statistic tends to have the lowest 192 power. This may suggest that the loss of information in using only rank information causes a decrease in 193 power.
194 As to our second objective, we evaluated the advantage of using an integrative approach by comparing 195 the FDR and power for GSAAzs-ks and three single-source methods: GSAA-SNP, GSEA, and 196 GSEAndes. Our results indicate that GSAAzs-ks substantially outperforms each of these three single data 197 type analyses (Table 1, Table S1). Overall, FDRs from GSAAzs-ks are consistently smaller than GSAA- 198 SNP, GSEA, and GSEAndes in all simulated scenarios. The power of GSAAzs-ks is also better than or 199 equal to those of single data type analyses in all simulated situations except for scenario S3 under the 200 odds ratio setting U [1.1, 1.3], in which GSAA-SNP is slightly better. Gene association scores calculated 201 by GSAAzs-ks are higher for genes with alterations in both gene expression and genotype compared to 202 genes with a single type of alteration. As expected, GSAAzs-ks performs better than single data type 203 analyses when all or part of causal genes contain both gene expression and genetic alterations (S1-S4). 204 GSAAzs-ks also shows increased ability to detect effects when the gene set includes both types of 205 alterations, but in which no single gene simultaneously contains both types (S5). GSAA-SNP 206 performance decreases when fewer genes are associated with phenotype (S2 and S5), and both variants of 207 GSEA suffer when fewer genes are differentially regulated (S3 and S5). Interestingly, the power of the 208 original GSEA substantially decreases when the causal gene set contains both up-regulated and down- 209 regulated genes (S4), but GSEAndes still retains power similar to scenario S1 in this case. Since both 210 GSAA and GSEAndes employ a non-directional differential expression score, there was no power loss 211 when up-regulation and down-regulation of genes coexist in the gene set.
212 Analyses of Glioblastoma Data
213 Human glioblastoma, the most common type of primary adult brain cancer, has been analyzed within 214 The Cancer Genome Atlas (TCGA) project. Several types of molecular data have been generated
7 215 including gene expression and SNP genotype data as well as DNA copy number and sequence data [31]. 216 We applied GSAAzs-ks, GSAA-SNP, GSEA, and GSEAndes to these data using gene sets from the 217 Molecular Signatures Database (MSigDB) that included 357 canonical pathways (see Methods and 218 Materials). We used GSAAzs-ks based on our simulations that indicated that the z-score based data 219 integration tends to have the highest ability to detect effects of association. Full results are shown in 220 Tables S2-S8. GSAAzs-ks identified 30 canonical pathways significantly associated with tumor samples 221 with FDR≤0.25 (Table 2, Table S2).
222 Initial integrative pathway analyses carried out by TCGA using sequence and DNA copy number data, 223 but not SNP genotype data, indicated three major pathways are frequently altered in glioblastoma: 224 RTK/RAS/PI3K signaling, p53 signaling, and RB signaling. Consistent with this, we identified multiple 225 pathways involved in different aspects of these three signaling pathways. Three pathways (Table2: G6, 226 G17, G21) contain core components of RTK/RAS/PI3K signaling (see Table S2 for genes in these 227 pathways). Pathways G17 and G21 directly describe PI3K/AKT signaling. PI3K acts as an upstream 228 activator of AKT that has pivotal roles in apoptosis, proliferation, and cell survival, and alterations of 229 genes in the PI3K/AKT pathway have been considered as causal forces underlying cancer [32,33]. 230 Pathway G6 is involved in the activation of the EGFR pathway. EGFR is reportedly over-expressed and 231 mutated in a significant proportion of glioblastoma [31,34].
232 Alterations in the p53 signaling and RB signaling are reflected by another group of pathways: G1, G12, 233 G19, and G23. These pathways are commensurate with a general oncogene-induced DNA damage model 234 for cancer development and progression uncovered by several experimental studies [35,36,37,38,39]. The 235 key contributors to the association of these pathways contain the core genes involved in checkpoint 236 response to DNA damage such as TP53, CHEK2 (also called CHK2), and ATM (Table S2). In addition, 237 the DNA damage model indicates the involvement of apoptosis and DNA replication in the oncogenesis. 238 A considerable number of significant pathways in GSAA analysis are also related to apoptosis (G4, G5, 239 G8, G9, G13, G15, G17, G21, G28) and DNA replication (G26, G27).
240 In addition to aberrations in well-known signaling pathways in glioblastoma, GSAA analysis also 241 suggested a role for the family of ATP-binding cassette (ABC) transporters, the second-ranked pathway 242 (G2). Gene expression profiles of many ABC transporter genes were significantly altered in tumor 243 samples. Some genes, such as ABCB7 and ABCC4, were up-regulated while others, for example ABCC8 244 and ABCG4, were down-regulated. Significantly associated genomic variants were found in several of 245 these genes including ABCB7 (SNP_A-8504624: p=1.0E-4) and ABCC4 (SNP_A-1811852: p=1.0E-4). 246 Normal and cancer stem cells have been shown to express high levels of ABC transporters that are 247 normally inactive in more mature cells, and the over-expression of specific ATP transporters has been 248 found to significantly affect the chemoresistance phenotype of cancer cells [40,41].
249 GSAA analysis also found a connection between the coagulation system and glioblastoma, represented 250 by the signaling pathway involved in platelet activation (G3) and the intrinsic prothrombin activation 251 pathway (G30). Patients with cancer, especially glioblastoma, have been shown to have increased risk for 252 thrombosis, characterized by alterations in normal blood flow, injury to the vascular endothelium, and 253 alterations in the constitution of blood [42,43]. Glioblastoma cells were also found to become both 254 procoagulant and hypersensitive to TF/PAR-mediated signaling. This transformation was thought to be 255 driven by the expression of EGFR and the most common EGFR mutant, EGFRvIII [44]. In addition, our
8 256 analysis indicated that the coagulation factor receptor F2R (also called PAR1) is the most significant up- 257 regulated gene in glioblastoma samples. F2R is also significantly associated in the SNP-based test 258 (SNP_A-8666280: p=1.0E-4). F2R is functional in glioblastoma cells and can mediate anti-apoptotic 259 signaling in the nervous system [45,46].
260 Interestingly, three pathways (G14, G16, G25) are associated with three neurodegenerative diseases, 261 Alzheimer's Disease, Dentatorubral-pallidoluysian Atrophy, and Huntington's Disease respectively. This 262 may suggest that glioblastoma disrupts the micro-environment of the brain leading to the differential 263 regulation of genes in these gene sets. Another identified gene set represents the gene network underlying 264 thyroid cancer (G22) that has common components with other cancer types. Three remaining pathways 265 (G7, G20, G24) are involved in sugar metabolism as well as nicotinate and nicotinamide metabolism.
266 Although our primary interest was to identify pathways associated with tumor samples, it was 267 informative to investigate pathways associated with normal samples. A total of 71 pathways were 268 identified associated with normal samples at FDR≤0.25 (Table S3). Perturbations in calcium-mediated 269 signal transduction pathways may be involved in the pathogenesis of glioblastoma since the top three 270 pathways are calcineurin-mediated pathways and a large number of other pathways (G5, G6, G10, G12, 271 G13, G16, G17, G20, G22, G23, G24, G25, G28, G30, G31, G37, G40, G42, G43, G46, G49, G50, G53, 272 G55, G61, G62) are also calcium/calmodulin-dependent. The expression level of catalytic subunit A of 273 calcineurin (PPP3CA) and some genes in the families of calmodulins and calcium/calmodulin-dependent 274 protein kinases, for example CALM1, CALM2, CALM3, CAMK2A, CAMK2B, were down-regulated in 275 tumor tissues. Some genes also include statistically significant genomic variants, such as PPP3CA 276 (SNP_A-8662814: p=1.0E-4) and CALM1 (SNP_A-4282870: p=1.0E-4). It has been shown that a high 277 level of activity of calcineurin predisposes neuronal cells to apoptosis [47,48]. Calcium-mediated 278 signaling also has a role in the regulation of cell cycle [49,50]. In addition, some top pathways are related 279 to the release of neurotransmitters such as glutamate (G1, G5) and ATPase signaling (G8, G14, G18, 280 G19). These results suggest that these particular processes were down-regulated in diseased tissues.
281 Neither GSEA nor GSAA-SNP identified significant pathways associated with tumor samples at FDR ≤ 282 0.25 (Tables S4, S6). However, in both GSEA and GSAA-SNP, the ten most significant pathways 283 included ones related to cell cycle checkpoints and the coagulation system. GSEA also reported pathways 284 involved in apoptosis and DNA replication while PI3K/AKT signaling pathways were highly ranked by 285 GSAA-SNP. Similar pathways as those found significantly associated with normal samples by GSAA 286 were likewise identified by GSEA (Tables S3, S5). GSEAndes did not identify any pathways as 287 significant in either direction (Tables S7-S8).
288 Analyses of Crohn’s DiseaseData
289 To explore the performance of GSAA within the context of a non-cancer complex disease, we applied 290 GSAAzs-ks, GSAA-SNP, GSEA, and GSEAndes to previously published gene expression and SNP 291 genotype data from patients with and without Crohn’s disease (CD). As before, MSigDB canonical 292 pathways (352) were used for this analysis. Full results are shown in Tables S9-S15. GSAA analysis 293 identified 12 canonical pathways significantly associated with case samples at FDR≤0.25 (Table 3, Table 294 S9).
9 295 Proteasome activity was found to be highly associated with disease as the first and ninth most 296 significant pathways were directly related to the proteasome complex. Recent studies have demonstrated 297 that the transcription factor NF-κB is a key regulator of epithelial integrity and intestinal immune 298 homeostasis [51,52,53,54,55]. Deficiency in or hyperactivation of NF-κB is one of the core mechanisms 299 leading to chronic inflammatory bowel disease (IBD). NF-κB signaling is primarily regulated by 300 inhibitory IB proteins and the IB kinase complex. Proteasomes play a crucial role in the degradation of 301 inhibitory IB proteins and the activation of NF-B [54,56,57]. We found that most of the proteasome- 302 related genes were up-regulated in disease samples including PSMB8 (also called LMP7) and PSMB9 303 (also called LMP2). PSMB9 also contains a significant genomic variant (SNP_A-2289910: p=0.0108). 304 PSMB8 and PSMB9 are two subunits of the immunoproteasome encoded by the HLA region and are 305 required for the degradation of phosphorylated IB proteins and for processing of NF-B precursor 306 [56,58]. Over-expression of immunoproteasomes in the inflamed intestine of CD patients has been 307 observed in multiple studies and has been found correlated to the excessive NF-κB activation [56,59,60]. 308 In addition, there is increasing evidence that a bacterial or viral infection and the host reaction to that 309 infection play an important role in the onset of Crohn’s disease [61]. Immunoproteasomes can be induced 310 and replace standard proteasomes quickly in response to the viral infection [62]. This process involves the 311 rapid expression of immunoproteasomes, possibly explaining the relevance of two high-ranked pathways 312 related to aminoacyl-tRNA biosynthesis (Table 3).
313 A gene set describing the molecular network underlying type I diabetes (T1D) ranked fifth among 314 canonical pathways. This pathway includes a large number of genes belonging to the HLA system (see 315 Table S9 for genes in this pathway). The HLA system encodes cell surface molecules specialized to 316 present antigenic peptides to the T-cell receptor (TCR) on T cells, and plays a critical role in the immune 317 system and autoimmunity [63,64]. It has been shown that T1D and inflammatory bowel disease share 318 common susceptibility pathways [65]. Multiple loci within HLA genomic region have been reported to be 319 associated with CD [66,67,68,69], and additional susceptibility loci may remain undiscovered.
320 GSAA found five pathways, in addition to the T1D pathway (G5), that are relevant to immune response 321 (G2, G6, G7, G8, G12). Thrombopoietin Signaling (G10) was also found associated with disease and this 322 signaling pathway has been previously reported to be disturbed in CD [70].
323 Fifteen pathways were significantly associated with control samples at FDR ≤ 0.25 (Table S10). Seven 324 (G1, G2, G3, G4, G6, G7, G10) are related to G protein-coupled receptor (GPCR) signaling or PI3K/AKT 325 signaling. GPCRs are upstream regulators of PI3K/AKT signaling. PI3K has important roles in 326 lymphocyte development, differentiation, and activation [71,72]. Multiple studies have shown the 327 correlation between PI3K pathway and IBD [73,74].
328 GSEA analysis identified 17 pathways significantly associated with case samples at FDR ≤ 0.25 (Table 329 S11). Except for two proteasome pathways (G4, G8), GSEA identified multiple additional pathways 330 involving the activation of NF-κB. The RelA (G3) and NF-κB (G14) pathways describe the actual NF-κB 331 signaling. The NTHi pathway (G17) describes the induction of an inflammatory response through 332 activation of NF-κB triggered by bacterial infection. Six pathways (G1, G5, G6, G7, G13, G17) contain 333 genes that participate in the immune system or inflammatory response. In addition, another identified 334 pathway (G11) is responsible for the activation of matrix metalloproteinases and the degradation of the 335 extracellular matrix. It has been shown that TNF mediated up-regulation of matrix metalloproteinases
10 336 results in severe damage of the extracellular matrix and mucosal degradation [54,75]. Altered apoptosis 337 pathway (G10) may contribute to inappropriate T cell accumulation and subsequently chronic 338 inflammation [76]. Only one of the pathways associated with control samples 339 (ST_WNT_CA2_CYCLIC_GMP_PATHWAY) reached significance in the gene expression analysis of 340 GSEA (Table S12). GSAA-SNP identified seven significant pathways, of which four (G1, G2, G6, G7) 341 are related to PI3K signaling (Table S13). GSEAndes identified four significant pathways of which the 342 top three were proteasome pathways (Table S14). The fourth is related to the activation of matrix 343 metalloproteinases also suggested by GSEA. No pathways associated with normal samples reached 344 significance in the GSEAndes analysis (Table S15).
345 Discussion
346 Genome-wide gene expression profiling and genotyping offer unparalleled opportunities to elucidate the 347 underlying mechanisms of complex traits or diseases. In this study, we developed a novel statistical 348 framework that simultaneously integrates gene expression data and genotype data into genome-wide 349 association analysis of biological pathways or gene sets. Combining evidence from these two genomic 350 data sources facilitates identification of genes with differential gene expression, genetic alterations, or 351 both characteristics that are associated with phenotypic traits. Results from our simulation study and the 352 analyses of glioblastoma and Crohn’s disease data showed that GSAA captured association signals that 353 occur in either type of genomic data as well as across both genomic data sources.
354 Many known functionally relevant variants are deleterious with minor allele frequencies of less than 5% 355 and therefore are not well represented on SNP chips used in GWAS. However, new sequencing 356 technologies are enabling the better identification of both common variants and rare variants. An area of 357 future development is to adapt GSAA to detect associations of both common variants and rare variants in 358 gene sets by integrating sequence analysis and gene expression analysis. There is no conceptual 359 difference between using sequence data and SNP data in our method. GSAA is well suited to capture 360 concordant association signals over a gene set or multiple loci even if the association information carried 361 by each gene or locus is weak. This is a key strength of GSAA since current research has shown that 362 some complex human diseases arise not from a few of common variants but instead are triggered by 363 multiple rare variants, each with a low marginal effect [77,78,79]. Similarly, other genomic data such as 364 copy number variation, methylation, and microRNA expression will be explored as inputs to GSAA.
365 GSAA requires a mapping of SNPs to genes. Currently, it is not known exactly what genomic regions 366 affect the function of each particular gene. In our analyses, we assigned SNPs that were within 1kb 367 upstream of the TSS to the end of the transcribed bases to a gene. We know that for many cases, this may 368 not include variants in distal regulatory regions hundreds of kilobases away that influence gene 369 expression levels, but it should include those in the core and proximal promoter regions and part of those 370 in the distal promoter [80]. This mapping can include information about distal regulatory variants if they 371 are in LD with those included in our mapping intervals or if they are within the mapping intervals of other 372 genes in the gene set. In previous studies, Wang et al. [18] mapped SNPs to the closest gene. Peng et al. 373 [19] used all SNPs within a gene to represent that gene. Our GSAA software provides users the ability to 374 define their own SNP mapping criteria by specifying how many base pairs upstream and/or downstream 375 of a gene a SNP must be included. Hopefully, the current influx of functional genomic data, especially 376 chromatin data, will eventually allow more accurate mappings.
11 377 The optimal way to assess the joint contribution of multiple SNPs mapped to the same gene in 378 association analysis is unknown. The region of association for a gene may harbor only one risk variant or 379 may harbor multiple risk variants that independently contribute to the overall association signal. 380 Compared to test statistics that combine correlation scores or p-values across all SNPs, we believe the 381 maximum statistic we used can more effectively eliminate the negative effects of correlation structure 382 between SNPs and differences in SNP set size on association inference. This maximum statistic should be 383 the best way to measure single risk variant association signals because multiple markers in strong LD 384 with the risk variant may artificially inflate the association. However, this statistic cannot accurately 385 capture the overall association information when multiple independent risk variants coexist. GSAA would 386 benefit by the development of new algorithms that more effectively assess joint contributions of SNPs to 387 the trait variation. Given its modular framework, new algorithms like these could be easily incorporated.
388 Gene set association analysis takes advantage of prior knowledge of biological pathways. Operating at 389 the pathway level aids in interpreting results, especially across different experimental platforms or 390 strategies. However, this currently creates a dependence on a priori knowledge. Inaccurate or incomplete 391 information about these pathways may lead to inaccurate association inferences. With the accumulation of 392 our knowledge on biological processes, pathway annotations are becoming increasingly more accurate 393 which will continue to increase the power of gene set association tests.
394 In summary, we report here a novel statistical framework that is capable of effectively identifying the 395 biological pathways/gene sets associated with complex traits or diseases by integrating genetic and gene 396 expression evidence into genome-wide association analysis of gene sets. Compared to gene set methods 397 that use only one genomic data type, our proposed method reduces the FDR in all simulated scenarios and 398 increases the power in nearly all simulated scenarios. In real settings, it not only confirmed the 399 associations of well-known pathways, but also provided new insights into the etiology of disease.
400 Materials and Methods
401 Gene Set Association Analysis
402 GSAA is based on multi-layer or hierarchical association tests. The advantage of a multi-layer approach 403 is that evidence for an association signal is aggregated from individual SNPs to individual genes to gene 404 sets. See Figure 1 for a graphical overview of the method. The methodology formulated here is for the 405 case where samples belong to one of two phenotypic classes. This multi-level procedure consists of five 406 individual calculations: 1) computation of a differential gene expression score; 2) computation of a single- 407 SNP association score; 3) computation of a SNP set association score; 4) computation of a gene 408 association score; and 5) a gene set association test. The following describes each of these in detail.
409 Differential Gene Expression Score
410 The differential expression score reflects the degree to which a gene is differentially expressed between 411 two phenotypic classes. It can be computed by a variety of suitable test statistics. In this work, the test 412 statistic used is the difference of the class means scaled by the standard deviation. The absolute 413 magnitude of the statistic indicates the strength of the correlation between the gene expression profile and 414 the phenotype, and the sign indicates the direction of this correlation. In our software, we provide five
12 415 different statistics that can be used to calculate this differential expression score, similar to GSEA (see 416 Document S1 for more details).
417 Single-SNP Association Score
418 Five different methods to calculate single-SNP association scores are provided in our software: a 419 genotype-based chi-square statistic; an allele-based chi-square statistic; a statistic based on frequency 420 differences in major/minor alleles between the two classes; and two statistics extended from genotype- 421 based and allele-based chi-square statistics, respectively (see Document S1 for more details). Other 422 suitable test statistics for the categorical phenotypes can be used. Results described in this paper 423 employed the allele-based chi-square statistic because it had greater power than genotype-based chi- 424 square statistic for our simulated SNP data that were based on an additive model (data not shown).
425 SNP Set Association Score
426 Gene expression data naturally allows for the calculation of a gene-based score. This is more 427 complicated for genotype data since in general multiple SNPs cover each gene and its regulatory region. 428 To assign SNPs to genes, we define a genomic interval encompassing each gene and some specified 429 number of bases upstream and downstream of the transcribed region. All SNPs within this interval are 430 used to represent the gene. Given these SNPs, we calculate a SNP set association score for a gene using a 431 maximum statistic. The maximum statistic is the maximum single-SNP score over all the SNPs assigned 432 to the gene.
433 Gene Association Score
434 The differential gene expression score and SNP set association score for each gene are combined to 435 generate a single gene association score. This composite correlation integrates evidence for association 436 across the gene expression and SNP data. The differential gene expression scores employed by GSEA [4] 437 have directionality – positive values indicate greater expression in class one while negative values 438 indicate greater expression in class two, therefore the weighted K-S test used in GSEA analysis may only 439 capture differential expression signals from one direction. However, genes in the same pathway are not 440 always differentially expressed in the same direction. Some pathways may contain both up-regulated and 441 down-regulated genes associated with the disease condition.
442 The directionality derived from the SNP-based test is not biologically meaningful because for each 443 locus it is not known which allele is actually associated with disease. For the SNP set association scores, 444 we do not know the directionality.
445 Therefore, we take the absolute values of the differential gene expression scores before data integration 446 in order to capture both up-regulation and down-regulation in pathways and to be consistent with the form 447 of SNP set association scores. Directionality is then resolved at the gene set association test step below. In 448 GSAA, three methods are used to integrate the evidence from gene expression analysis and SNP analysis 449 to produce gene association scores.
450 (1) Z-score sum
13 451 For each differential expression score or SNP set association score, we first generate its null distribution 452 by a phenotype-based permutation procedure. Then, we standardize these scores by the mean and
453 standard deviation of its null distribution. More specifically, suppose {e1,..., eN } are the absolute values
454 of differential expression scores for N genes and {s1,..., sN } are the SNP set association scores for the
455 same genes. The standard expression scores {ze1,...,zeN } are computed as
ei - me 456 zei = s e
457 and the standard SNP set association scores {zs1,..., zsN } for the same genes are similarly computed as
si - ms 458 zsi = s s
459 where (e , s ) and ( e , s ) are the means and standard deviations of the null distributions
460 corresponding to ei and si , respectively. This transformation brings the scores from different statistical 461 tests or on different scales onto a common scale so that these scores are directly comparable with each 462 other. The z-score transformation results in both positive values and negative values. We are not looking 463 for a statistic with directionality, so we need to shift the z-scores to be positive. This is done by adding a 464 constant c that is the absolute value of the most negative score across all standard gene expression scores 465 and standard SNP set association scores.
466 The gene association scores are the sum of these standard scores gi (zei c) (zsi c) .
467 (2) Fisher’s method
468 For each differential gene expression score and SNP set association score, we first generate its null 469 distribution by a phenotype-based permutation procedure, and then we estimate its p-value by comparing 470 the score with its null distribution. Fisher’s method [19,81], also known as Fisher's combined probability 471 test, is used to combine p-values from the expression-based test and the SNP-based test to produce the 472 integrative gene association score:
K
473 gi = -2åloge (pij ) j =1
474 where K is the number of independent tests, in this case K 2 , namely expression-based test and SNP-
475 based test, and pij is the p-value for gene i in test j.
476 (3) Rank sum
477 For each differential expression score or SNP set association score, we first generate its null distribution 478 by a phenotype-based permutation procedure, and then we transform every score and its corresponding
14 479 null scores into ranks. Tied values are assigned the average of the applicable ranks. For example, (2, 5, 6, 480 5) is ranked as (1, 2.5, 4, 2.5). Gene association scores are then computed as
481 gi rei rsi
482 where rei and rsi are the ranks of gene i in the expression-based test and SNP-based test, respectively.
483 Gene Set Association Test
484 Given the gene association scores, we use a weighted Kolmogorov-Smirnov (K-S) test to determine 485 which gene sets have the greatest combined evidence for association with the given phenotype. 486 Essentially, the weighted K-S test determines for each gene set whether the genes belonging to that gene 487 set are preferentially near the top of the ranked ordered list based on gene association scores. More 488 formally, given a particular gene set S including H genes and the rank ordered gene association scores
489 {g1,..., g N } for all genes in the expression data set, a running association score RASS i)( for the rank 490 ordered genes in positions i 1,..., N is computed as
1 i 1 i N 491 RASS i)( | g j | I( j S) I( j S), N S | g j | I( j S), NS j1 N H j1 j1
492 Where I ( j S) is an indicator variable that is one if the jth gene in the rank ordered list is in gene set S 493 and otherwise zero. Similarly, I ( j S) takes the value of zero if the jth gene is in the gene set and is 494 otherwise one. The gene set association score, AS(S) , is the maximum deviation from zero of the 495 running association score over the positions i 1,..., N
496 AS(S) max i1,...,N [RASS (i)], AS(S) min i1,..., N [RAS S (i)].
497
498 Finally, if | AS(S) || AS(S) |then the final gene set association score AS(S) AS(S) , otherwise
499 AS(S) AS(S) .
500 The gene association scores we used lack directionality, so a negative AS(S) means there is no 501 association between the gene set and the phenotype. We here set AS(S) = 0.0001 if AS(S)<0 so the 502 negative AS scores will not confuse the following assignment of the direction. One advantage for the 503 standard GSEA analysis is that its association score suggests the direction of an association. In the K-S 504 test used by GSAA to calculate the integrative gene set association score, we aim to capture both up- 505 regulated and down-regulated genes in a gene set, so we do not assign directionality at this point. Instead, 506 we perform an additional K-S test based solely on the directed differential gene expression scores to get a 507 corresponding expression-based association score (EAS) for each gene set. We impose directionality on 508 the integrative AS based on the sign of the EAS for the same gene set, AS(S) = AS(S)´sign(EAS(S)).
509 In GSAA, we integrate gene expression information and genotype information at the gene level. 510 However, some genes may not have associated SNPs. For these genes, the gene association score is just
15 511 derived from the expression-based test. To account for possible heterogeneity of information at each gene 512 locus, we standardize the original gene association scores by the mean and standard deviations of its null 513 distribution using the same method as we used to calculate the standard expression score before 514 performing the K-S test.
515 The absolute magnitude of the AS score indicates the strength of the association between the gene set 516 and the phenotype, and the sign indicates which phenotypic class the gene set is associated with. Finally a 517 normalized association score (NAS) for each gene set is calculated to adjust for difference in gene set size. 518 Same as GSEA, we use a mean-based method and normalize the positive and negative scores separately.
519 Assessment of Statistical Significance and Adjustment for Multiple Hypothesis Testing
520 We assess the statistical significance of the gene set association score and adjust for multiple hypothesis 521 testing based on a phenotype-based permutation procedure. This procedure preserves LD structure in SNP 522 data and gene-gene correlation structure in gene expression data. A nominal p-value is calculated relative 523 to a null distribution generated by shuffling the phenotypic class labels and recalculating the gene set 524 association score many times. If the gene expression and SNP data come from the same samples, matched 525 data, GSAA will perform better. Since it may be difficult to obtain matched genomic data and to be able 526 to use GSAA on existing GWA and gene expression data that may not be matched we designed GSAA to 527 allow for both matched and unmatched data. When the data are matched, permutations for the expression- 528 based test and SNP-based test are not independent and GSAA uses the same permutation template for 529 both. This can result in greater power to identify real associations.
530 We use the false discovery rate (FDR) and the family-wise error rate (FWER) based on the normalized 531 gene set association scores to correct for multiple hypothesis testing and to control the proportion of false
532 positives below a certain threshold. Given m gene sets {S1,..., Sm} and label permutations 1,...,
533 the FDR for each gene set Si with NAS(Si ) 0 is computed as
% of NAS(S j , ) NAS(Si ) for j 1,..., m and 1,..., 534 FDR(Si ) , % of NAS(S j ) NAS(Si ) for j i
535 If NAS(Si ) 0 , the FDR is computed as
% of NAS(S j , ) NAS(Si ) for j 1,..., m and 1,..., 536 FDR(Si ) , % of NAS(S j ) NAS(Si ) for j i
537 Where NAS (S j , ) is the normalized association score for gene set j with label permutation .
538 NAS(S j , ) and NAS(S j , ) denote positive and negative NAS (S j , ) , respectively. NAS (S j ) is
539 the normalized association score for gene set j . NAS(S j ) , NAS(S j ) denote positive and negative
540 NAS (S j ) , respectively.
541 The FWER for a gene set Si with NAS(Si ) 0 is computed as
16 542 FWER(Si ) % of [max j1,...,m [NAS(S j , ) ]] NAS(Si ) for 1,..., .
543 If NAS(Si ) 0 , the FDR is computed as
544 FWER(Si ) % of [min j1,...,m [NAS(S j , ) ]] NAS(Si ) for 1,..., .
545 Computational Efficiency of GSAA
546 With respect to computational efficiency, GSAA took approximately 0.9 hrs and 4 hrs for the analyses 547 of glioblastoma data and Crohn’s disease data respectively using one computational node with 8 548 processors (Intel(R) Xeon(R) CPU E5520 @ 2.27GHz). It only took about 3.5 mins for our simulated 549 datasets. For other information about running GSAA software, see GSAA User Guide at 550 http://gsaa.genome.duke.edu/userguide_gsaa.html for details.
551 Gene Set Association Analysis-SNP (GSAA-SNP)
552 GSAA-SNP was created to perform gene set association analysis based solely on SNP data. In GSAA- 553 SNP, we remove the module of the differential expression test in GSAAzs-ks and use the original SNP set 554 association score as the gene association score. Otherwise it is same as GSAAzs-ks.
555 Gene Set Enrichment Analysis Based on Non-directional Differential Expression Scores (GSEAndes)
556 Both GSAA and GSAA-SNP are based on the non-directional association analysis at the gene level. To 557 compare them with the GSEA more fairly we created GSEAndes. GSEAndes is an extension of the 558 original GSEA software and also an expression-based version of GSAAzs-ks. In GSEAndes, we remove 559 the two modules of single-SNP association test and SNP set association test in GSAAzs-ks, and use the 560 original differential expression score as the gene association score. Otherwise it is same as GSAAzs-ks.
561 Generation of Simulated Data
562 We generated simulated gene expression data and SNP genotype data to study the power of various 563 integrative methods and single-source methods. Modeling a case-control setting, we simulated 200 cases 564 and 200 controls for each data set.
565 Gene Set Data
566 For each simulation we generated 100 gene sets. Only the first gene set (causal gene set) included risk 567 genes. We used P53PATHWAY containing 16 genes from the Molecular Signatures Database (MSigDB, 568 http://www.broadinstitute.org/gsea/msigdb/index.jsp) as a prototype to simulate the causal gene set. The 569 gene expression and genotype information of P53PATHWAY were obtained from the glioblastoma data 570 generated through The Cancer Genome Atlas (TCGA, http://cancergenome.nih.gov) project. The 571 remaining 99 gene sets were simulated from null models, namely none of genes in these gene sets were 572 associated with the phenotype of interest with respect to gene expression profiles or genotypes. The sizes 573 of null gene sets were randomly drawn from U [15, 30]. Genes within null gene sets were randomly 574 drawn from a pool of 984 non-causal genes.
575 SNP Data
17 576 Each simulated SNP data set included 1000 genes, each gene with one genotyped SNP for a total of 577 1000 SNPs. Some of these SNPs were considered causally related to the phenotype of interest. We 578 simulated the causal SNPs in the causal gene set based on the genotype information of P53PATHWAY. 579 We first assigned SNPs that were within the region 1 kilobase pair (kb) upstream of the transcription start 580 site (TSS) to the end of the transcribed bases to each gene in the P53PATHWAY, then we removed SNPs 581 with minor allele frequency (MAF) less than 0.05 and chose the SNP with the highest score in chi-square 582 test as the tag SNP of the gene. We set the allele frequencies of causal SNPs in the simulated causal gene 583 set same as the allele frequencies of corresponding tag SNPs in the P53PATHWAY. The heterozygote 584 odds ratio for each causal SNP was generated from U [1.1, 1.3] and U [1.2, 1.4] respectively. We used an 585 additive disease model for the causal loci and the disease prevalence was set to 0.05. To build a full 586 spectrum of allele frequencies, we drew minor allele frequencies from U [0.01, 0.50] for the null SNPs 587 with no association with the phenotype. Based on these parameter settings, the genotype data were 588 generated by PLINK [82] (http://pngu.mgh.harvard.edu/purcell/plink/). We then assigned the case-control 589 status based on the model
N 590 logit{Pr(Y =1)} = x b + e . j åi=1 Gji i j
591 Where N is the number of causal SNPs in the causal gene set. x denotes the coding of the genotype at G ji
592 causal SNP i for sample j with effect size i which is the log odds ratio at SNP i . e j denotes a random
593 sample-specific error term for sample j , e j is sampled from a standard normal distribution.
594 Gene Expression Data
595 Each simulated gene expression data set consisted of 1000 genes corresponding to the 1000 genes in the 596 SNP data set. Some of these genes were considered risk genes that were differentially expressed in cases 597 and controls. We first generated baseline expression levels for genes in the causal gene set from a 598 multivariate normal distribution X ~ N(,) . The mean vector and the covariance matrix were 599 estimated from the P53PATHWAY based on the glioblastoma data. Next, we added disease effect to the 600 causal genes in the causal gene set based on the model x = x (1+ x b), where x is the expression ji 0 G ji ji 601 level of gene i in sample j , x is the baseline expression level of gene i in sample j , x denotes the 0 G ji 602 coding of the genotype at SNP i for sample j in the SNP data. is the effect size of the genotype on 603 gene expression and reflects the degree to which the gene expression is correlated with the genotype of 604 tag SNP of the same gene. was drawn from either U [0.3, 0.5] or U [-0.3, -0.5]. The sign of 605 indicates up or down-regulation of the gene. In our simulation, gene expression variations of a causal 606 gene in the expression data were determined by the genotypes of the same gene in the SNP data. However, 607 it is not realistic that all causal genes contain both gene expression variation and genotypic variation 608 associated with the phenotype. To address this issue, we also simulated scenarios where some causal 609 genes contain only gene expression variation and others include just genotypic variation. In the former 610 case, we first simulated a causal SNP in the SNP data set, and then simulated a causal gene in the 611 expression data set based on this causal SNP. Finally we replaced this SNP with a null SNP. In the latter 612 case, we only added disease effect to part of causal genes in the expression data set. Gene expression
18 613 values for null genes were also drawn from a multivariate normal distribution X 0 ~ N(0 ,0 ) . We 614 estimated the average values of means and variances of all genes in glioblastoma data and use these
615 average values to set 0 and 0 .
616 Glioblastoma and Crohn’s Disease Data
617 Data generated through The Cancer Genome Atlas (TCGA, http://cancergenome.nih.gov) project for 618 glioblastoma samples were obtained through their data portal. The expression data set includes 258 tumor 619 samples and 10 normal samples. The SNP data set includes 205 tumor samples and 89 normal samples. 620 For Crohn's disease (CD), expression data were generated by Wu et al [83], and is available in the NCBI 621 Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo, GSE6731). The expression data set 622 we used contains 23 samples with 7 cases versus 16 controls. Cases were obtained from biopsies from 623 affected regions of colons of CD patients. Controls were derived from biopsies from unaffected regions of 624 colons of CD patients and from the colons of healthy adults. The SNP data set includes 1748 cases and 625 2938 controls obtained from a published large-scale GWA study [84], available from the Wellcome Trust 626 Case Control Consortium (WTCCC, https://www.wtccc.org.uk/info/access_to_data_samples.shtml).
627 We imputed missing SNP data using fastPHASE 1.4.0 [85] 628 (http://depts.washington.edu/uwc4c/express-licenses/assets/fastphase). We assigned SNPs that were 629 within the region 1kb upstream of the TSS to the end of the transcribed bases to be associated with a gene. 630 Although 1kb upstream of the TSS may be insufficient to cover the entire regulatory regions for all genes, 631 it should include both the core and proximal promoter regions and at least some of the distal regulatory 632 elements [80]. The canonical pathways from the Molecular Signatures Database (MSigDB, 633 http://www.broadinstitute.org/gsea/msigdb/index.jsp) were used in this analysis. Pathways with less than 634 15 genes or more than 100 genes in the expression dataset were filtered to avoid overly narrow or broad 635 functional categories. This resulted in 357 canonical pathways for glioblastoma data and 352 canonical 636 pathways for the Crohn’s disease data. Data for genes not contained in any of the gene sets were filtered 637 prior to performing GSAA analysis since these data would not affect the gene set association analysis. We 638 assessed the statistical significance of association scores of gene sets and adjusted for multiple hypothesis 639 testing using 10,000 permutations of phenotypic class labels.
640 Acknowledgments
641 We thank the three anonymous reviewers for their constructive comments and suggestions that greatly 642 improved our manuscript. We thank Xuejun Qin (Duke University) for discussions on simulations. We 643 thank Nianjun Liu (University of Alabama at Birmingham) for discussions on identifying the causal 644 variants. We thank Jenny Tung (The University of Chicago) for discussions on trait mapping. We thank 645 the GSEA team (Broad Institute) for providing GSEA software, code and documentation. We thank The 646 Cancer Genome Atlas (TCGA) and Wellcome Trust Case Control Consortium (WTCCC) for granting 647 access to the raw genotype and phenotype data.
648 References
649 1. Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, et al. (2009) Potential etiologic and 650 functional implications of genome-wide association loci for human diseases and traits. Proc Natl 651 Acad Sci U S A 106: 9362-9367.
19 652 2. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, et al. (2009) Finding the missing heritability 653 of complex diseases. Nature 461: 747-753. 654 3. Wang WY, Barratt BJ, Clayton DG, Todd JA (2005) Genome-wide association studies: theoretical and 655 practical concerns. Nat Rev Genet 6: 109-118. 656 4. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, et al. (2005) Gene set enrichment 657 analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc 658 Natl Acad Sci U S A 102: 15545-15550. 659 5. Dinu I, Potter JD, Mueller T, Liu Q, Adewale AJ, et al. (2007) Improving gene set analysis of microarray 660 data by SAM-GS. BMC Bioinformatics 8: 242. 661 6. Kim SY, Volsky DJ (2005) PAGE: parametric analysis of gene set enrichment. BMC Bioinformatics 6: 662 144. 663 7. Luo W, Friedman MS, Shedden K, Hankenson KD, Woolf PJ (2009) GAGE: generally applicable gene set 664 enrichment for pathway analysis. BMC Bioinformatics 10: 161. 665 8. Boorsma A, Foat BC, Vis D, Klis F, Bussemaker HJ (2005) T-profiler: scoring the activity of predefined 666 groups of genes using gene expression data. Nucleic Acids Res 33: W592-595. 667 9. Newton MA, Quintana FA, Den Boon JA, Sengupta S, Ahlquist P (2007) Random-set methods identify 668 distinct aspects of the enrichment signal in gene-set analysis. Ann Appl Stat 1: 85-106. 669 10. Goeman JJ, van de Geer SA, de Kort F, van Houwelingen HC (2004) A global test for groups of genes: 670 testing association with a clinical outcome. Bioinformatics 20: 93-99. 671 11. Mansmann U, Meister R (2005) Testing differential gene expression in functional groups. Goeman's 672 global test versus an ANCOVA approach. Methods Inf Med 44: 449-453. 673 12. Maglietta R, Piepoli A, Catalano D, Licciulli F, Carella M, et al. (2007) Statistical assessment of 674 functional categories of genes deregulated in pathological conditions by using microarray data. 675 Bioinformatics 23: 2063-2072. 676 13. Goeman JJ, Buhlmann P (2007) Analyzing gene expression data in terms of gene sets: methodological 677 issues. Bioinformatics 23: 980-987. 678 14. Allison DB, Cui X, Page GP, Sabripour M (2006) Microarray data analysis: from disarray to 679 consolidation and consensus. Nat Rev Genet 7: 55-65. 680 15. Khatri P, Draghici S (2005) Ontological analysis of gene expression data: current tools, limitations, 681 and open problems. Bioinformatics 21: 3587-3595. 682 16. Abatangelo L, Maglietta R, Distaso A, D'Addabbo A, Creanza TM, et al. (2009) Comparative study of 683 gene set enrichment methods. BMC Bioinformatics 10: 275. 684 17. Liu Q, Dinu I, Adewale AJ, Potter JD, Yasui Y (2007) Comparative evaluation of gene-set analysis 685 methods. BMC Bioinformatics 8: 431. 686 18. Wang K, Li M, Bucan M (2007) Pathway-Based Approaches for Analysis of Genomewide Association 687 Studies. Am J Hum Genet 81. 688 19. Peng G, Luo L, Siu H, Zhu Y, Hu P, et al. (2010) Gene and pathway-based second-wave analysis of 689 genome-wide association studies. Eur J Hum Genet 18: 111-117. 690 20. O'Dushlaine C, Kenny E, Heron EA, Segurado R, Gill M, et al. (2009) The SNP ratio test: pathway 691 analysis of genome-wide association datasets. Bioinformatics 25: 2762-2763. 692 21. Holden M, Deng S, Wojnowski L, Kulle B (2008) GSEA-SNP: applying gene set enrichment analysis to 693 SNP data from genome-wide association studies. Bioinformatics 24: 2784-2785. 694 22. Chen LS, Hutter CM, Potter JD, Liu Y, Prentice RL, et al. (2010) Insights into colon cancer etiology via a 695 regularized approach to gene set analysis of GWAS data. Am J Hum Genet 86: 860-871. 696 23. Zhong H, Yang X, Kaplan LM, Molony C, Schadt EE (2010) Integrating Pathway Analysis and Genetics 697 of Gene Expression for Genome-wide Association Studies. Am J Hum Genet. 698 24. De la Cruz O, Wen X, Ke B, Song M, Nicolae DL (2010) Gene, region and pathway level analyses in 699 whole-genome studies. Genet Epidemiol 34: 222-231.
20 700 25. Zhang L, Guo YF, Liu YZ, Liu YJ, Xiong DH, et al. (2010) Pathway-based genome-wide association 701 analysis identified the importance of regulation-of-autophagy pathway for ultradistal radius 702 BMD. J Bone Miner Res. 703 26. Baranzini SE, Galwey NW, Wang J, Khankhanian P, Lindberg R, et al. (2009) Pathway and network- 704 based analysis of genome-wide association studies in multiple sclerosis. Hum Mol Genet 18: 705 2078-2090. 706 27. Liu YJ, Guo YF, Zhang LS, Pei YF, Yu N, et al. (2010) Biological Pathway-Based Genome-Wide 707 Association Analysis Identified the Vasoactive Intestinal Peptide (VIP) Pathway Important for 708 Obesity. Obesity (Silver Spring). 709 28. Ooi CH, Ivanova T, Wu J, Lee M, Tan IB, et al. (2009) Oncogenic pathway combinations predict clinical 710 prognosis in gastric cancer. PLoS Genet 5: e1000676. 711 29. Gorlov IP, Gallick GE, Gorlova OY, Amos C, Logothetis CJ (2009) GWAS meets microarray: are the 712 results of genome-wide association studies and gene-expression profiling consistent? Prostate 713 cancer as an example. PLoS One 4: e6511. 714 30. Nicolae DL, Gamazon E, Zhang W, Duan S, Dolan ME, et al. (2010) Trait-associated SNPs are more 715 likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet 6. 716 31. (2008) Comprehensive genomic characterization defines human glioblastoma genes and core 717 pathways. Nature 455: 1061-1068. 718 32. Carnero A, Blanco-Aparicio C, Renner O, Link W, Leal JF (2008) The PTEN/PI3K/AKT signalling 719 pathway in cancer, therapeutic implications. Curr Cancer Drug Targets 8: 187-198. 720 33. Osaki M, Oshimura M, Ito H (2004) PI3K-Akt pathway: its functions and alterations in human cancer. 721 Apoptosis 9: 667-676. 722 34. Heimberger AB, Suki D, Yang D, Shi W, Aldape K (2005) The natural history of EGFR and EGFRvIII in 723 glioblastoma patients. J Transl Med 3: 38. 724 35. Halazonetis TD, Gorgoulis VG, Bartek J (2008) An oncogene-induced DNA damage model for cancer 725 development. Science 319: 1352-1355. 726 36. Bartkova J, Horejsi Z, Koed K, Kramer A, Tort F, et al. (2005) DNA damage response as a candidate 727 anti-cancer barrier in early human tumorigenesis. Nature 434: 864-870. 728 37. Kastan MB, Bartek J (2004) Cell-cycle checkpoints and cancer. Nature 432: 316-323. 729 38. Gorgoulis VG, Vassiliou LV, Karakaidos P, Zacharatos P, Kotsinas A, et al. (2005) Activation of the DNA 730 damage checkpoint and genomic instability in human precancerous lesions. Nature 434: 907- 731 913. 732 39. Venkitaraman AR (2005) Medicine: aborting the birth of cancer. Nature 434: 829-830. 733 40. Bronger H, Konig J, Kopplow K, Steiner HH, Ahmadi R, et al. (2005) ABCC drug efflux pumps and 734 organic anion uptake transporters in human gliomas and the blood-tumor barrier. Cancer Res 65: 735 11419-11428. 736 41. Bleau AM, Huse JT, Holland EC (2009) The ABCG2 resistance network of glioblastoma. Cell Cycle 8: 737 2936-2944. 738 42. Reynes G, Vila V, Martin M, Parada A, Fleitas T, et al. (2010) Circulating markers of angiogenesis, 739 inflammation, and coagulation in patients with glioblastoma. J Neurooncol. 740 43. Lyman GH, Khorana AA (2009) Cancer, clots and consensus: new understanding of an old problem. J 741 Clin Oncol 27: 4821-4826. 742 44. Magnus N, Garnier D, Rak J (2010) Oncogenic epidermal growth factor receptor up-regulates 743 multiple elements of the tissue factor signaling pathway in human glioma cells. Blood 116: 815- 744 818. 745 45. Junge CE, Lee CJ, Hubbard KB, Zhang Z, Olson JJ, et al. (2004) Protease-activated receptor-1 in human 746 brain: localization and functional expression in astrocytes. Exp Neurol 188: 94-103.
21 747 46. Guo H, Liu D, Gelbard H, Cheng T, Insalaco R, et al. (2004) Activated protein C prevents neuronal 748 apoptosis via protease activated receptors 1 and 3. Neuron 41: 563-572. 749 47. Asai A, Qiu J, Narita Y, Chi S, Saito N, et al. (1999) High level calcineurin activity predisposes neuronal 750 cells to apoptosis. J Biol Chem 274: 34450-34458. 751 48. Wang HG, Pathan N, Ethell IM, Krajewski S, Yamaguchi Y, et al. (1999) Ca2+-induced apoptosis 752 through calcineurin dephosphorylation of BAD. Science 284: 339-343. 753 49. Baksh S, DeCaprio JA, Burakoff SJ (2000) Calcineurin regulation of the mammalian G0/G1 checkpoint 754 element, cyclin dependent kinase 4. Oncogene 19: 2820-2827. 755 50. Kahl CR, Means AR (2003) Regulation of cell cycle progression by calcium/calmodulin-dependent 756 pathways. Endocr Rev 24: 719-736. 757 51. Ben-Neriah Y, Schmidt-Supprian M (2007) Epithelial NF-kappaB maintains host gut microflora 758 homeostasis. Nat Immunol 8: 479-481. 759 52. Nenci A, Becker C, Wullaert A, Gareus R, van Loo G, et al. (2007) Epithelial NEMO links innate 760 immunity to chronic intestinal inflammation. Nature 446: 557-561. 761 53. Zaph C, Troy AE, Taylor BC, Berman-Booty LD, Guild KJ, et al. (2007) Epithelial-cell-intrinsic IKK-beta 762 expression regulates intestinal immune homeostasis. Nature 446: 552-556. 763 54. Atreya I, Atreya R, Neurath MF (2008) NF-kappaB in inflammatory bowel disease. J Intern Med 263: 764 591-596. 765 55. Spehlmann ME, Eckmann L (2009) Nuclear factor-kappa B in intestinal protection and destruction. 766 Curr Opin Gastroenterol 25: 92-99. 767 56. Visekruna A, Joeris T, Seidel D, Kroesen A, Loddenkemper C, et al. (2006) Proteasome-mediated 768 degradation of IkappaBalpha and processing of p105 in Crohn disease and ulcerative colitis. J 769 Clin Invest 116: 3195-3203. 770 57. Mattson MP, Meffert MK (2006) Roles for NF-kappaB in nerve cell survival, plasticity, and disease. 771 Cell Death Differ 13: 852-860. 772 58. Hayashi T, Faustman D (2000) Essential role of human leukocyte antigen-encoded proteasome 773 subunits in NF-kappaB activation and prevention of tumor necrosis factor-alpha-induced 774 apoptosis. J Biol Chem 275: 5238-5247. 775 59. Visekruna A, Slavova N, Dullat S, Grone J, Kroesen AJ, et al. (2009) Expression of catalytic proteasome 776 subunits in the gut of patients with Crohn's disease. Int J Colorectal Dis 24: 1133-1139. 777 60. Visekruna A, Joeris T, Schmidt N, Lawrenz M, Ritz JP, et al. (2009) Comparative expression analysis 778 and characterization of 20S proteasomes in human intestinal tissues: The proteasome pattern as 779 diagnostic tool for IBD patients. Inflamm Bowel Dis 15: 526-533. 780 61. Irving PM, Gibson PR (2008) Infections and IBD. Nat Clin Pract Gastroenterol Hepatol 5: 18-27. 781 62. Yewdell JW (2005) Immunoproteasomes: regulating the regulator. Proc Natl Acad Sci U S A 102: 782 9089-9090. 783 63. Fernando MM, Stevens CR, Walsh EC, De Jager PL, Goyette P, et al. (2008) Defining the role of the 784 MHC in autoimmunity: a review and pooled analysis. PLoS Genet 4: e1000024. 785 64. Benacerraf B (1981) Role of MHC gene products in immune regulation. Science 212: 1229-1238. 786 65. Wang K, Baldassano R, Zhang H, Qu HQ, Imielinski M, et al. (2010) Comparative genetic analysis of 787 inflammatory bowel disease and type 1 diabetes implicates multiple loci with opposite effects. 788 Hum Mol Genet 19: 2059-2067. 789 66. Reinshagen M, Loeliger C, Kuehnl P, Weiss U, Manfras BJ, et al. (1996) HLA class II gene frequencies 790 in Crohn's disease: a population based analysis in Germany. Gut 38: 538-542. 791 67. Newman B, Silverberg MS, Gu X, Zhang Q, Lazaro A, et al. (2004) CARD15 and HLA DRB1 alleles 792 influence susceptibility and disease localization in Crohn's disease. Am J Gastroenterol 99: 306- 793 315.
22 794 68. Lombardi ML, Pirozzi G, Luongo V, Mercuro O, Pace E, et al. (2001) Crohn disease: susceptibility and 795 disease heterogeneity revealed by HLA genotyping. Hum Immunol 62: 701-704. 796 69. Forcione DG, Sands B, Isselbacher KJ, Rustgi A, Podolsky DK, et al. (1996) An increased risk of Crohn's 797 disease in individuals who inherit the HLA class II DRB3*0301 allele. Proc Natl Acad Sci U S A 93: 798 5094-5098. 799 70. Kapsoritakis AN, Potamianos SP, Sfiridaki AI, Koukourakis MI, Koutroubakis IE, et al. (2000) Elevated 800 thrombopoietin serum levels in patients with inflammatory bowel disease. Am J Gastroenterol 801 95: 3478-3481. 802 71. Okkenhaug K, Vanhaesebroeck B (2003) PI3K in lymphocyte development, differentiation and 803 activation. Nat Rev Immunol 3: 317-330. 804 72. Okkenhaug K, Fruman DA (2010) PI3Ks in lymphocyte signaling and development. Curr Top Microbiol 805 Immunol 346: 57-85. 806 73. Zhao L, Lee JY, Hwang DH (2008) The phosphatidylinositol 3-kinase/Akt pathway negatively regulates 807 Nod2-mediated NF-kappaB pathway. Biochem Pharmacol 75: 1515-1525. 808 74. Fukao T, Koyasu S (2003) PI3K and negative regulation of TLR signaling. Trends Immunol 24: 358-363. 809 75. Pallone F, Monteleone G (2001) Mechanisms of tissue damage in inflammatory bowel disease. Curr 810 Opin Gastroenterol 17: 307-312. 811 76. Ina K, Itoh J, Fukushima K, Kusugami K, Yamaguchi T, et al. (1999) Resistance of Crohn's disease T 812 cells to multiple apoptotic signals is associated with a Bcl-2/Bax mucosal imbalance. J Immunol 813 163: 1081-1090. 814 77. Robinson R (2010) Common disease, multiple rare (and distant) variants. PLoS Biol 8: e1000293. 815 78. Gorlov IP, Gorlova OY, Sunyaev SR, Spitz MR, Amos CI (2008) Shifting paradigm of association studies: 816 value of rare single-nucleotide polymorphisms. Am J Hum Genet 82: 100-112. 817 79. Kryukov GV, Pennacchio LA, Sunyaev SR (2007) Most rare missense alleles are deleterious in humans: 818 implications for complex disease and association studies. Am J Hum Genet 80: 727-739. 819 80. Bortoluzzi S, Coppe A, Bisognin A, Pizzi C, Danieli GA (2005) A multistep bioinformatic approach 820 detects putative regulatory elements in gene promoters. BMC Bioinformatics 6: 121. 821 81. Fisher RA (1932) Statistical methods for research workers. Edinburgh etc.: Oliver and Boyd. xiii p., 1 l. 822 p. 823 82. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, et al. (2007) PLINK: a tool set for whole- 824 genome association and population-based linkage analyses. Am J Hum Genet 81: 559-575. 825 83. Wu F, Dassopoulos T, Cope L, Maitra A, Brant SR, et al. (2007) Genome-wide gene expression 826 differences in Crohn's disease and ulcerative colitis from endoscopic pinch biopsies: insights into 827 distinctive pathogenesis. Inflamm Bowel Dis 13: 807-821. 828 84. (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared 829 controls. Nature 447: 661-678. 830 85. Scheet P, Stephens M (2006) A fast and flexible statistical model for large-scale population genotype 831 data: applications to inferring missing genotypes and haplotypic phase. Am J Hum Genet 78: 832 629-644. 833 834 835
23 836 837 Figure 1. Overview of GSAA. Differential gene expression scores are computed for each gene from gene 838 expression profiles (left). Independently, SNP set association scores for each gene are likewise computed 839 based on the SNPs assigned to the respective gene (right). The gene association scores integrate evidence 840 from both the expression signature and the genotype signature for each gene. Finally, the pathway 841 association test identifies gene sets associated with samples of a single phenotype by integrating evidence 842 across genes in the gene sets. 843 844
24 845 Table 1. Simulation results based on scenarios S1-S5. GSAAzs-ks GSAAfm-ks GSAArs-ks Scenario P-value FDR FWER Power P-value FDR FWER Power P-value FDR FWER Power S1 0.00148 0.00863 0.00678 0.995 0.00234 0.01149 0.01135 0.99 0.02466 0.20581 0.21401 0.88 S2 0.00655 0.03329 0.04047 0.975 0.00612 0.04201 0.04615 0.975 0.07287 0.41050 0.44442 0.635 S3 0.00700 0.01636 0.01626 0.985 0.01034 0.03689 0.03419 0.97 0.07256 0.39251 0.41371 0.64 S4 0.00131 0.00717 0.00626 0.995 0.00222 0.00947 0.00898 0.995 0.02485 0.22870 0.22102 0.85 S5 0.01392 0.06284 0.06845 0.965 0.01871 0.10183 0.10235 0.945 0.14096 0.58146 0.64715 0.375 GSAA-SNP GSEA GSEAndes Scenario P-value FDR FWER Power P-value FDR FWER Power P-value FDR FWER Power S1 0.00214 0.06329 0.06246 0.99 0.00575 0.20613 0.19597 0.975 0.00572 0.33766 0.33049 0.975 S2 0.02534 0.33123 0.36035 0.835 0.00491 0.19031 0.18211 0.985 0.00484 0.28920 0.30796 0.98 S3 0.00214 0.06329 0.06246 0.99 0.08099 0.59216 0.60453 0.62 0.05458 0.47899 0.51517 0.735 S4 0.00214 0.06329 0.06246 0.99 0.16346 0.80379 0.91396 0.22 0.00714 0.34753 0.34553 0.98 S5 0.03266 0.37309 0.39806 0.825 0.07435 0.54944 0.59846 0.585 0.04768 0.47577 0.48953 0.73 846 Three versions of GSAA were evaluated where each varied the summary statistic used for combining genetic and gene 847 expression evidence at the single gene level: GSAAzs-ks, GSAAfm-ks, and GSAArs-ks. Also shown are results for GSAA-SNP, 848 GSEA, and GSEAndes. For these simulations, the odds ratios for causal loci were drawn from U [1.1, 1.3] and 200 simulated 849 replicates were used. 850 851
25 852 Table 2. Significant pathways associated with glioblastoma tumor samples (FDR≤0.25).
Index Gene Set Name P-value FDR Function G1 G2PATHWAY 0.0039 0.1707 cell cycle checkpoints, DNA damage response G2 HSA02010_ABC_TRANSPORTERS_GENERAL 0.0032 0.1870 ATP binding G3 SPPAPATHWAY 0.0008 0.1890 thrombin signaling, blood coagulation G4 RELAPATHWAY 0.0083 0.1894 proliferation, migration and apoptosis G5 CERAMIDEPATHWAY 0.0012 0.1929 apoptosis, cellular differentiation, proliferation G6 CARDIACEGFPATHWAY 0.0171 0.2001 EGFR signaling G7 HSA00531_GLYCOSAMINOGLYCAN_DEGRADATION 0.0462 0.2024 glycosaminoglycan degradation G8 NFKBPATHWAY 0.0159 0.2036 proliferation, migration and apoptosis G9 STRESSPATHWAY 0.0054 0.2084 apoptosis G10 INTEGRINPATHWAY 0.0204 0.2170 cellular shape, mobility, cell cycle G11 HCMVPATHWAY 0.0130 0.2211 proliferation, viral replication G12 RACCYCDPATHWAY 0.0328 0.2211 cell cycle G13 FASPATHWAY 0.0288 0.2242 apoptosis G14 HSA05010_ALZHEIMERS_DISEASE 0.0315 0.2257 alzheimer's disease G15 TNFR1PATHWAY 0.0056 0.2258 apoptosis G16 HSA05050_DENTATORUBROPALLIDOLUYSIAN_ATROPHY 0.0516 0.2261 dentatorubral-pallidoluysian atrophy, apoptosis G17 AKTPATHWAY 0.0443 0.2271 PI3K/AKT signaling, apoptosis, proliferation G18 ST_ERK1_ERK2_MAPK_PATHWAY 0.0121 0.2308 ERK1/ERK2 MAPK signaling G19 ARFPATHWAY 0.0591 0.2312 cell cycle checkpoints, DNA damage response G20 FRUCTOSE_AND_MANNOSE_METABOLISM 0.0328 0.2313 fructose and mannose metabolism G21 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES 0.0175 0.2318 PI3K/AKT signaling, apoptosis, proliferation G22 HSA05216_THYROID_CANCER 0.0293 0.2322 thyroid cancer G23 ATMPATHWAY 0.0500 0.2323 cell cycle checkpoints, DNA damage response G24 HSA00760_NICOTINATE_AND_NICOTINAMIDE_METABOLISM 0.0644 0.2327 nicotinate and nicotinamide metabolism G25 HSA05040_HUNTINGTONS_DISEASE 0.0104 0.2356 huntington disease G26 DNA_REPLICATION_REACTOME 0.0972 0.2357 DNA replication G27 TELPATHWAY 0.0466 0.2394 DNA replication, cell division G28 TNFR2PATHWAY 0.0702 0.2459 apoptosis, proliferation G29 IL7PATHWAY 0.1214 0.2466 B and T cell development G30 INTRINSICPATHWAY 0.0325 0.2470 thrombin signaling, blood coagulation 853 For full results, see Table S2. 854 855
26 856 Table 3. Significant pathways associated with case samples (FDR≤0.25).
Index Gene Set Name P-value FDR Function G1 PROTEASOME 0.0455 0.0469 activation of NF-κB chemotaxis, G-protein signaling, G2 ST_G_ALPHA_I_PATHWAY 0.0002 0.0500 immune response G3 AMINOACYL_TRNA_BIOSYNTHESIS 0.0018 0.0529 tRNA biosynthesis G4 HSA00970_AMINOACYL_TRNA_BIOSYNTHESIS 0.0076 0.0573 tRNA biosynthesis autoimmunity, immune response, G5 HSA04940_TYPE_I_DIABETES_MELLITUS 0.0002 0.0586 inflammation G6 SIG_BCR_SIGNALING_PATHWAY 0.0002 0.0657 immune response chemotaxis, G-protein signaling, G7 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_CHEMOTAXIS_PATHWAY 0.0000 0.0682 immune response G8 SA_B_CELL_RECEPTOR_COMPLEXES 0.0015 0.1142 immune response G9 PROTEASOMEPATHWAY 0.0724 0.1148 activation of NF-κB G10 TPOPATHWAY 0.0046 0.1957 thrombopoietin Signaling G11 HSA00565_ETHER_LIPID_METABOLISM 0.0115 0.1997 ether lipid metabolism G12 HSA04514_CELL_ADHESION_MOLECULES 0.0000 0.2345 immune response, inflammation 857 For full results, see Table S9. 858 859
27 Figure Click here to download high resolution image Table S1 ClickTable.htm here to download Table: Table S1.pdf 2/24/11 10:58 AM
Table S1. Simulation results based on scenarios S1-S5. Three versions of GSAA were evaluated where each varied the summary test statistic used for combining genetic and gene expression evidence at the single gene level: GSAAzs-ks, GSAAfm-ks, and GSAArs-ks. Also shown are results for GSAA-SNP, GSEA, and GSEAndes. For these simulations, the odds ratios for causal loci were drawn from U [1.2, 1.4] and 200 simulated replicates were used. GSAAzs-ks GSAAfm-ks GSAArs-ks Scenario P-value FDR FWER Power P-value FDR FWER Power P-value FDR FWER Power S1 0.00004 0.00006 0.00005 1 0.00021 0.00031 0.0003 1 0.00838 0.09763 0.08681 0.96 S2 0.00086 0.00556 0.00476 1 0.00142 0.00919 0.0081 1 0.04306 0.32386 0.35302 0.74 S3 0.00015 0.00029 0.00029 1 0.00103 0.0031 0.00286 1 0.04322 0.29625 0.30615 0.745 S4 0.00004 0.00006 0.00007 1 0.00021 0.0003 0.00035 1 0.00901 0.10076 0.09669 0.96 S5 0.00196 0.01421 0.01524 0.99 0.00409 0.0301 0.03028 0.99 0.08832 0.46426 0.49206 0.56 GSAA-SNP GSEA GSEAndes Scenario P-value FDR FWER Power P-value FDR FWER Power P-value FDR FWER Power S1 0.00022 0.01081 0.0105 1 0.00135 0.08897 0.08861 0.995 0.0012 0.15822 0.15415 1 S2 0.00383 0.12071 0.12295 0.99 0.00136 0.09411 0.09194 0.995 0.00114 0.17817 0.16221 1 S3 0.00022 0.01081 0.0105 1 0.03389 0.42584 0.45186 0.76 0.01621 0.32445 0.32579 0.92 S4 0.00022 0.01081 0.0105 1 0.09459 0.74475 0.82412 0.435 0.00084 0.14502 0.13888 1 S5 0.0107 0.18058 0.19928 0.945 0.03872 0.44853 0.45944 0.755 0.01727 0.27594 0.27716 0.885
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S2a ClickTable.htm here to download Table: Table S2a.pdf 2/24/11 3:56 PM
Table S2a. Canonical pathways associated with tumor samples in GSAAzs-ks (glioblastoma) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 G2PATHWAY 23 0.003867403 0.17072165 0.4057 G2 HSA02010_ABC_TRANSPORTERS_GENERAL 35 0.003195526 0.18701257 0.7718 G3 SPPAPATHWAY 20 0.000750047 0.18901698 0.1305 G4 RELAPATHWAY 16 0.008267641 0.18935044 0.3522 G5 CERAMIDEPATHWAY 22 0.001211632 0.19291803 0.254 G6 CARDIACEGFPATHWAY 17 0.017138598 0.2001259 0.5894 G7 HSA00531_GLYCOSAMINOGLYCAN_DEGRADATION 16 0.046165302 0.20241573 0.7676 G8 NFKBPATHWAY 23 0.015904183 0.20356141 0.7381 G9 STRESSPATHWAY 24 0.005410822 0.2084124 0.6583 G10 INTEGRINPATHWAY 32 0.0203958 0.21704605 0.9799 G11 HCMVPATHWAY 15 0.012999247 0.22105286 0.5619 G12 RACCYCDPATHWAY 22 0.0328341 0.22107548 0.9782 G13 FASPATHWAY 27 0.02880576 0.22415315 0.9727 G14 HSA05010_ALZHEIMERS_DISEASE 24 0.031506587 0.2256697 0.9767 G15 TNFR1PATHWAY 28 0.005638341 0.22580703 0.7337 G16 HSA05050_DENTATORUBROPALLIDOLUYSIAN_ATROPHY 15 0.051597502 0.22610396 0.9341 G17 AKTPATHWAY 17 0.04431818 0.22709373 0.9631 G18 ST_ERK1_ERK2_MAPK_PATHWAY 29 0.012149716 0.23078054 0.9595 G19 ARFPATHWAY 15 0.05912826 0.23120965 0.9858 G20 FRUCTOSE_AND_MANNOSE_METABOLISM 24 0.032815535 0.23129167 0.9725 G21 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES 34 0.017493272 0.2317714 0.9693 G22 HSA05216_THYROID_CANCER 29 0.029270172 0.23219422 0.9886 G23 ATMPATHWAY 19 0.050038345 0.23226443 0.9563 G24 HSA00760_NICOTINATE_AND_NICOTINAMIDE_METABOLISM 16 0.06441048 0.23274952 0.9875 G25 HSA05040_HUNTINGTONS_DISEASE 27 0.010383236 0.23559128 0.9316 G26 DNA_REPLICATION_REACTOME 43 0.09718045 0.23571183 0.9537 G27 TELPATHWAY 15 0.046620484 0.23935968 0.9245 G28 TNFR2PATHWAY 18 0.070219316 0.24587418 0.9918 G29 IL7PATHWAY 16 0.121409215 0.24660425 0.9922 G30 INTRINSICPATHWAY 22 0.03246878 0.24701856 0.9532 G31 VEGFPATHWAY 27 0.010980392 0.25345898 0.9236 G32 HSA04512_ECM_RECEPTOR_INTERACTION 80 0.034577064 0.25670275 0.9933 G33 CELLCYCLEPATHWAY 22 0.028148148 0.26240826 0.918 G34 G1PATHWAY 25 0.059898287 0.26292533 0.9965 G35 SPRYPATHWAY 16 0.09894819 0.26338795 0.9969 G36 PROSTAGLANDIN_SYNTHESIS_REGULATION 27 0.052980132 0.26803556 0.9963 G37 HSA01032_GLYCAN_STRUCTURES_DEGRADATION 26 0.08297201 0.27400923 0.996 G38 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS 32 0.04727133 0.27447116 0.9978 G39 CELL_CYCLE_KEGG 79 0.09419582 0.27477267 0.9982 G40 CARM_ERPATHWAY 26 0.020408163 0.27947012 0.9152 G41 TOLLPATHWAY 30 0.01740162 0.29048362 0.9085 G42 RIBOSOMAL_PROTEINS 81 0.15738499 0.2999938 0.9993 G43 APOPTOSIS_GENMAPP 42 0.047647767 0.30000973 0.9995 G44 INTEGRIN_MEDIATED_CELL_ADHESION_KEGG 83 0.017653981 0.30075815 0.9995 G45 ST_FAS_SIGNALING_PATHWAY 59 0.023864958 0.30331838 0.9995 G46 HSA05219_BLADDER_CANCER 41 0.029187333 0.3034758 0.9994
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 6 Table.htm 2/24/11 3:56 PM
G47 ST_P38_MAPK_PATHWAY 35 0.037567776 0.3044782 0.9994 G48 HSA05221_ACUTE_MYELOID_LEUKEMIA 52 0.019317959 0.3049734 0.9993 G49 HSA04662_B_CELL_RECEPTOR_SIGNALING_PATHWAY 59 0.034897476 0.30555102 0.9994 G50 HSA04330_NOTCH_SIGNALING_PATHWAY 37 0.04475854 0.30664933 0.9994 G51 HSA03030_DNA_POLYMERASE 21 0.16178937 0.3213609 0.9999 G52 GALACTOSE_METABOLISM 22 0.10415459 0.32694343 0.9999 G53 TIDPATHWAY 17 0.15406808 0.3290897 0.9999 G54 HSA00051_FRUCTOSE_AND_MANNOSE_METABOLISM 36 0.0682955 0.33231756 0.9999 G55 RASPATHWAY 22 0.1148048 0.338605 1 G56 BLOOD_CLOTTING_CASCADE 19 0.16402628 0.3388418 1 G57 HSA05220_CHRONIC_MYELOID_LEUKEMIA 74 0.02411091 0.35264832 1 G58 IL1RPATHWAY 30 0.10578576 0.3547687 1 G59 ECMPATHWAY 21 0.15345667 0.35727915 1 G60 STARCH_AND_SUCROSE_METABOLISM 29 0.11369972 0.35908917 1 G61 HSA00510_N_GLYCAN_BIOSYNTHESIS 32 0.111330435 0.36508286 1 G62 HSA03010_RIBOSOME 55 0.23647751 0.3704401 1 G63 HSA05213_ENDOMETRIAL_CANCER 50 0.055845723 0.37079522 1 G64 HSA04670_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION 100 0.042379625 0.37133738 1 G65 MCALPAINPATHWAY 22 0.1554054 0.37305868 1 G66 ATRBRCAPATHWAY 20 0.24455611 0.37331986 1 G67 HSA01030_GLYCAN_STRUCTURES_BIOSYNTHESIS_1 81 0.051022395 0.37524515 1 G68 HSA04210_APOPTOSIS 78 0.04700162 0.376139 1 G69 HSA05222_SMALL_CELL_LUNG_CANCER 87 0.045568563 0.3762021 1 G70 HSA05223_NON_SMALL_CELL_LUNG_CANCER 52 0.091216214 0.40506843 1 G71 CASPASEPATHWAY 22 0.20391773 0.4068784 1 G72 STATIN_PATHWAY_PHARMGKB 16 0.27625263 0.40895262 1 G73 HSA00052_GALACTOSE_METABOLISM 27 0.16625024 0.41035053 1 G74 HIVNEFPATHWAY 54 0.087220244 0.41354132 1 G75 HSA00591_LINOLEIC_ACID_METABOLISM 27 0.17818323 0.41356716 1 G76 HSA00590_ARACHIDONIC_ACID_METABOLISM 48 0.10269426 0.41512072 1 G77 HSA05210_COLORECTAL_CANCER 81 0.07032833 0.42754126 1 G78 HSA05212_PANCREATIC_CANCER 71 0.084604435 0.42958447 1 G79 HSP27PATHWAY 15 0.26584205 0.4318151 1 G80 EICOSANOID_SYNTHESIS 16 0.29635036 0.43720365 1 G81 G1_TO_S_CELL_CYCLE_REACTOME 61 0.18379824 0.44260773 1 G82 N_GLYCAN_BIOSYNTHESIS 21 0.24623777 0.44390637 1 G83 HSA05131_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EPEC 41 0.16926932 0.44865578 1 G84 HSA04940_TYPE_I_DIABETES_MELLITUS 39 0.22908522 0.4495839 1 G85 HSA05130_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EHEC 41 0.16926932 0.4539341 1 G86 CHEMICALPATHWAY 21 0.24450812 0.4583339 1 G87 DEATHPATHWAY 32 0.20978197 0.47424835 1 G88 PROSTAGLANDIN_AND_LEUKOTRIENE_METABOLISM 30 0.23503023 0.49311984 1 G89 PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 18 0.30688447 0.49501115 1 G90 MTORPATHWAY 23 0.28702438 0.49661845 1 G91 GLYCOSPHINGOLIPID_METABOLISM 21 0.30506182 0.5115792 1 G92 BREAST_CANCER_ESTROGEN_SIGNALING 91 0.16669886 0.5127232 1 G93 41BBPATHWAY 18 0.32528713 0.5142569 1 G94 APOPTOSIS 66 0.19491354 0.5197143 1 G95 APOPTOSIS_KEGG 48 0.20627989 0.5235496 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 6 Table.htm 2/24/11 3:56 PM
G96 P53PATHWAY 16 0.38441795 0.5270048 1 G97 HSA00530_AMINOSUGARS_METABOLISM 26 0.30676466 0.5465801 1 G98 HYPERTROPHY_MODEL 19 0.3551892 0.55008197 1 G99 HSA04115_P53_SIGNALING_PATHWAY 62 0.2493401 0.56117284 1 G100 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY 97 0.25147116 0.56255996 1 G101 IL6PATHWAY 21 0.37211916 0.5628371 1 G102 GSK3PATHWAY 25 0.3312338 0.56345075 1 G103 HSA00240_PYRIMIDINE_METABOLISM 70 0.25619334 0.5640034 1 G104 HSA05215_PROSTATE_CANCER 84 0.2224934 0.56609756 1 G105 HSA05217_BASAL_CELL_CARCINOMA 45 0.2724557 0.5681483 1 G106 IL2RBPATHWAY 34 0.33750734 0.5898921 1 G107 IGF1MTORPATHWAY 20 0.39785153 0.5905404 1 G108 UBIQUITIN_MEDIATED_PROTEOLYSIS 21 0.41030127 0.5920173 1 G109 HSA00512_O_GLYCAN_BIOSYNTHESIS 20 0.4045671 0.6006414 1 G110 HSA04610_COMPLEMENT_AND_COAGULATION_CASCADES 64 0.32537788 0.6018306 1 G111 IL3PATHWAY 15 0.4666176 0.6030576 1 G112 NTHIPATHWAY 21 0.42892343 0.6043836 1 G113 MITOCHONDRIAL_FATTY_ACID_BETAOXIDATION 15 0.4563396 0.60705924 1 G114 HSA00500_STARCH_AND_SUCROSE_METABOLISM 59 0.32392305 0.6076561 1 G115 HSA00563_GLYCOSYLPHOSPHATIDYLINOSITOL_ANCHOR_BIOSYNT18 0.4503902 0.6161121 1 G116 LAIRPATHWAY 15 0.5104549 0.6437622 1 G117 HSA00565_ETHER_LIPID_METABOLISM 27 0.43121743 0.6450222 1 G118 HSA00450_SELENOAMINO_ACID_METABOLISM 24 0.4362035 0.64784795 1 G119 STEMPATHWAY 15 0.5003694 0.6495991 1 G120 CSKPATHWAY 20 0.5091502 0.6583453 1 G121 PITX2PATHWAY 16 0.51181835 0.66009563 1 G122 HSA00030_PENTOSE_PHOSPHATE_PATHWAY 25 0.4632326 0.6611265 1 G123 AMIPATHWAY 20 0.5091502 0.6636977 1 G124 TRANSLATION_FACTORS 43 0.4617481 0.66695625 1 G125 AMINOACYL_TRNA_BIOSYNTHESIS 20 0.5210401 0.6764809 1 G126 SA_CASPASE_CASCADE 16 0.5415189 0.68826485 1 G127 ST_TUMOR_NECROSIS_FACTOR_PATHWAY 29 0.4963475 0.6898624 1 G128 PROTEASOME 16 0.5495705 0.6922055 1 G129 LYSINE_DEGRADATION 28 0.50493544 0.6929462 1 G130 CTLA4PATHWAY 17 0.5726912 0.70776504 1 G131 UCALPAINPATHWAY 15 0.5766396 0.7154472 1 G132 P53HYPOXIAPATHWAY 18 0.57174885 0.7257063 1 G133 HSA00903_LIMONENE_AND_PINENE_DEGRADATION 24 0.56967133 0.7390772 1 G134 HSA00790_FOLATE_BIOSYNTHESIS 35 0.5556434 0.74137515 1 G135 PYRIMIDINE_METABOLISM 55 0.5442778 0.74325854 1 G136 PROTEASOMEPATHWAY 21 0.59309834 0.76705015 1 G137 TH1TH2PATHWAY 17 0.6159027 0.7711961 1 G138 ST_INTERLEUKIN_4_PATHWAY 26 0.6495023 0.81715906 1 G139 HSA00770_PANTOTHENATE_AND_COA_BIOSYNTHESIS 15 0.6858974 0.8674211 1 G140 HSA04612_ANTIGEN_PROCESSING_AND_PRESENTATION 73 0.6497873 0.8707649 1 G141 HSA04640_HEMATOPOIETIC_CELL_LINEAGE 80 0.7158893 0.8769326 1 G142 ALKPATHWAY 32 0.7321497 0.8838343 1 G143 HSA00271_METHIONINE_METABOLISM 16 0.7250529 0.8852411 1 G144 HSA00624_1_AND_2_METHYLNAPHTHALENE_DEGRADATION 16 0.7349489 0.8878181 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 6 Table.htm 2/24/11 3:56 PM
G145 HSA00970_AMINOACYL_TRNA_BIOSYNTHESIS 26 0.71639377 0.8892985 1 G146 HSA04950_MATURITY_ONSET_DIABETES_OF_THE_YOUNG 18 0.71529907 0.891234 1 G147 NKTPATHWAY 25 0.74547225 0.89274615 1 G148 HSA00632_BENZOATE_DEGRADATION_VIA_COA_LIGATION 23 0.7371174 0.89290774 1 G149 HSA00310_LYSINE_DEGRADATION 40 0.8 0.9052523 1 G150 HSA04350_TGF_BETA_SIGNALING_PATHWAY 81 0.8528331 0.91068906 1 G151 HSA00120_BILE_ACID_BIOSYNTHESIS 31 0.81577927 0.91489756 1 G152 INFLAMPATHWAY 29 0.8231671 0.9161992 1 G153 HSA00071_FATTY_ACID_METABOLISM 39 0.8149914 0.9167484 1 G154 HSA00220_UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS27 0.8031098 0.91727626 1 G155 TOB1PATHWAY 16 0.7683563 0.91772735 1 G156 HSA03020_RNA_POLYMERASE 18 0.75613385 0.9185276 1 G157 OVARIAN_INFERTILITY_GENES 23 0.8022541 0.92030185 1 G158 MITOCHONDRIAPATHWAY 20 0.8292209 0.93174297 1 G159 HSA03022_BASAL_TRANSCRIPTION_FACTORS 28 0.855258 0.93877214 1 G160 GLYCINE_SERINE_AND_THREONINE_METABOLISM 30 0.8809332 0.94016063 1 G161 RARRXRPATHWAY 15 0.80431575 0.94514996 1 G162 HSA00260_GLYCINE_SERINE_AND_THREONINE_METABOLISM 36 0.8910218 0.94589704 1 G163 RNA_TRANSCRIPTION_REACTOME 33 0.8791039 0.9461959 1 G164 HSA00480_GLUTATHIONE_METABOLISM 32 0.96047354 0.9885715 1 G165 GLUTATHIONE_METABOLISM 27 0.9495991 0.9910209 1 G166 ARAPPATHWAY 20 1 1 1 G167 CHOLESTEROL_BIOSYNTHESIS 15 1 1 1 G168 CYTOKINEPATHWAY 20 1 1 1 G169 DCPATHWAY 20 1 1 1 G170 HSA00100_BIOSYNTHESIS_OF_STEROIDS 23 1 1 1 G171 HSA00361_GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION19 1 1 1 G172 HSA00860_PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 27 1 1 1 G173 HSA03050_PROTEASOME 22 1 1 1 G174 HSA04614_RENIN_ANGIOTENSIN_SYSTEM 15 1 1 1 G175 SMALL_LIGAND_GPCRS 17 1 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 6 Table.htm 2/24/11 3:56 PM
file:///Users/sayan/Desktop/Qing/Table.htm Page 5 of 6 Table.htm 2/24/11 3:56 PM
file:///Users/sayan/Desktop/Qing/Table.htm Page 6 of 6 Table S2b ClickTable.htm here to download Table: Table S2b.pdf 2/24/11 3:59 PM
Table S2b. Canonical pathways associated with tumor samples in GSAAzs-ks (glioblastoma) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 BIOCARTA_G2_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_G2_PATHWAY.html G2 KEGG_ABC_TRANSPORTERS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_ABC_TRANSPORTERS.html G3 BIOCARTA_SPPA_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_SPPA_PATHWAY.html G4 BIOCARTA_RELA_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_RELA_PATHWAY.html G5 BIOCARTA_CERAMIDE_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CERAMIDE_PATHWAY.html G6 BIOCARTA_CARDIACEGF_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CARDIACEGF_PATHWAY.html G7 KEGG_GLYCOSAMINOGLYCAN_DEGRADATION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GLYCOSAMINOGLYCAN_DEGRADATION.html G8 BIOCARTA_NFKB_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NFKB_PATHWAY.html G9 BIOCARTA_STRESS_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_STRESS_PATHWAY.html G10 BIOCARTA_INTEGRIN_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_INTEGRIN_PATHWAY.html G11 BIOCARTA_HCMV_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_HCMV_PATHWAY.html G12 BIOCARTA_RACCYCD_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_RACCYCD_PATHWAY.html G13 BIOCARTA_FAS_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_FAS_PATHWAY.html G14 KEGG_ALZHEIMERS_DISEASE http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_ALZHEIMERS_DISEASE.html G15 BIOCARTA_TNFR1_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_TNFR1_PATHWAY.html G16 N/A N/A G17 BIOCARTA_AKT_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_AKT_PATHWAY.html G18 ST_ERK1_ERK2_MAPK_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_ERK1_ERK2_MAPK_PATHWAY.html G19 BIOCARTA_ARF_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_ARF_PATHWAY.html G20 KEGG_FRUCTOSE_AND_MANNOSE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_FRUCTOSE_AND_MANNOSE_METABOLISM.html G21 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES http://www.broadinstitute.org/gsea/msigdb/cards/SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES.html G22 KEGG_THYROID_CANCER http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_THYROID_CANCER.html G23 BIOCARTA_ATM_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_ATM_PATHWAY.html G24 KEGG_NICOTINATE_AND_NICOTINAMIDE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_NICOTINATE_AND_NICOTINAMIDE_METABOLISM.html G25 KEGG_HUNTINGTONS_DISEASE http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_HUNTINGTONS_DISEASE.html G26 KEGG_DNA_REPLICATION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_DNA_REPLICATION.html G27 BIOCARTA_TEL_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_TEL_PATHWAY.html G28 BIOCARTA_TNFR2_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_TNFR2_PATHWAY.html G29 BIOCARTA_IL7_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_IL7_PATHWAY.html G30 BIOCARTA_INTRINSIC_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_INTRINSIC_PATHWAY.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S2c ClickTable.htm here to download Table: Table S2c.pdf 2/24/11 4:19 PM
Table S2c. Canonical pathways associated with tumor samples in GSAAzs-ks (glioblastoma) Sorted by FDR Index Description G1 Activated Cdc2-cyclin B kinase regulates the G2/M transition; DNA damage stimulates the DNA-PK/ATM/ATR kinases, which inactivate Cdc2. G2 Genes involved in ABC transporters - general G3 Thrombin cleaves protease-activated receptors PAR1 and PAR4 to induce calcium influx and activate platelet aggregation, a process inhibited by aspirin. G4 Acetylated NF-kB proteins are immune to IkB regulation and promote transcription until the histone deacetylase HDAC3 deacetylates the RelA subunit of NF-kB. G5 Ceramide is a lipid signaling molecule that can activate proliferative or apoptotic pathways, depending on signaling context, localization, and cell type. G6 Cardiac hypertrophy, a response to high blood pressure, is stimulated by GPCR ligands such as angiotensin II that activate the EGF pathway. G7 Genes involved in glycosaminoglycan degradation G8 Inactive nuclear factor kB (NF-kB) is inhibited by the IkB family in the cytoplasm; active NF-kB is localized in the nucleus and regulates transcription of a variety of genes. G9 Tumor necrosis factor receptor TNFR1 promotes apoptosis and activates the pro-inflammatory NF-kB, while TNFR2 activates stress-activated protein kinases (SAPKs). G10 Integrins are cell surface receptors commonly present at focal adhensions that interact with the extracellular matrix and transduce extracellular signaling. G11 Cytomegalovirus activates MAP kinase pathways in the host cell, inducing transcription of viral genes. G12 Ras, Rac, and Rho coordinate to induce cyclin D1 expression and activate cdk2 to promote the G1/S transition. G13 Binding of the Fas ligand to the Fas receptor induces caspase activation and consequent apoptosis in the Fas-expressing cell. G14 Genes involved in Alzheimer's disease G15 Tumor necrosis factor alpha binds to its receptor TNFR1 and induces caspase-dependent apoptosis. G16 Genes involved in dentatorubropallidoluysian atrophy (DRPLA) G17 Second messenger PIP3 promotes cell survival by activating the anti-apoptotic kinase AKT. G18 The Erk1 and Erk2 MAP kinase pathways are regulated by Raf, Mos, and Tpl-2. G19 Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. G20 G21 Genes related to PIP3 signaling in B lymphocytes G22 Genes involved in thyroid cancer G23 The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. G24 Genes involved in nicotinate and nicotinamide metabolism G25 Genes involved in Huntington's disease G26 G27 Telomerase is a ribonucleotide protein that adds telomeric repeats to the 3' ends of chromosomes. G28 Tumor necrosis factor beta, produced by activated lymphocytes, binds to its receptor TNFR2 to induce activation in immune cells and apoptosis in many other cells. G29 IL-7 is required for B and T cell development and proliferation and may contribute to activation of VDJ recombination. G30 The intrinsic prothrombin activation pathway is activated by traumatized blood vessels and induces clot formation.
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S2d Click here to download Table: Table S2d.pdf
Table S2. Canonical pathways associated with tumor samples in GSAAzs-ks (glioblastoma)
Sorted by FDR
Index Genes
G1 ATM ATR BRCA1 CCNB1 CDC2 CDC25A CDC25B CDC25C CDC34 CDKN1A CDKN2D CHEK1 CHEK2 EP300 GADD45A MDM2 MYT1 PLK PRKDC RPS6KA1 TP53 WEE1 YWHAH YWHAQ
G2 ABCA1 ABCA10 ABCA12 ABCA13 ABCA2 ABCA3 ABCA4 ABCA5 ABCA6 ABCA7 ABCA8 ABCA9 ABCB1 ABCB10 ABCB11 ABCB4 ABCB5 ABCB6 ABCB7 ABCB8 ABCB9 ABCC1 ABCC10 ABCC11 ABCC12 ABCC2 ABCC3 ABCC4 ABCC5 ABCC6 ABCC8 ABCC9 ABCD1 ABCD2 ABCD3 ABCD4 ABCG1 ABCG2 ABCG4 ABCG5 ABCG8 CFTR TAP1 TAP2 G3 F2 F2R F2RL3 GNAI1 GNB1 GNGT1 HRAS ITGA1 ITGB1 MAP2K1 MAPK1 MAPK3 PLA2G4A PLCB1 PRKCA PRKCB1 PTGS1 PTK2 RAF1 SRC SYK TBXAS1
G4 CHUK CREBBP EP300 FADD HDAC3 IKBKB IKBKG NFKB1 NFKBIA RELA RIPK1 TNF TNFRSF1A TNFRSF1B TRADD TRAF6
G5 BAD BAX BCL2 CASP8 CYCS FADD MAP2K1 MAP2K4 MAP3K1 MAPK1 MAPK3 MAPK8 NFKB1 NSMAF PDCD8 RAF1 RELA RIPK1 SMPD1 TNFRSF1A TRADD TRAF2
G6 ADAM12 AGT AGTR2 ARHA EDN1 EDNRA EDNRB EGF EGFR FOS HRAS JUN MYC NFKB1 PLCG1 PRKCA PRKCB1 RELA
G7 ARSB GALNS GLB1 GNS GUSB HEXA HEXB HGSNAT HPSE HPSE2 HYAL1 HYAL2 IDS IDUA LCT NAGLU SPAM1
G8 CHUK FADD IKBKB IKBKG IL1A IL1R1 IRAK1 MAP3K1 MAP3K14 MAP3K7 MAP3K7IP1 MYD88 NFKB1 NFKBIA RELA RIPK1 TLR4 TNF TNFAIP3 TNFRSF1A TNFRSF1B TRADD TRAF6
G9 ATF1 CASP2 CHUK CRADD IKBKB IKBKG JUN LTA MAP2K3 MAP2K4 MAP2K6 MAP3K1 MAP3K14 MAP4K2 MAPK14 MAPK8 NFKB1 NFKBIA RELA RIPK1 TANK TNF TNFRSF1A TRADD TRAF2
G10 ACTA1 ACTN1 ACTN2 ACTN3 ARHA BCAR1 BCR CAPN1 CAPNS1 CAPNS2 CAV1 CRKL CSK FYN GRB2 GRF2 HRAS ITGA1 ITGB1 JUN MAP2K1 MAP2K2 MAPK1 MAPK3 MAPK8 PPP1R12B PTK2 PXN RAF1 RAP1A ROCK1 SHC1 SOS1 SRC TLN1 TNS VCL ZYX G11 AKT1 CREB1 MAP2K1 MAP2K2 MAP2K3 MAP2K6 MAP3K1 MAPK1 MAPK14 MAPK3 NFKB1 PIK3CA PIK3R1 RB1 RELA SP1
G12 AKT1 ARHA CCND1 CCNE1 CDK2 CDK4 CDK6 CDKN1A CDKN1B E2F1 HRAS MAPK1 MAPK3 NFKB1 NFKBIA PAK1 PIK3CA PIK3R1 RAC1 RAF1 RB1 RELA TFDP1
G13 ADPRT ARHGDIB CASP10 CASP3 CASP6 CASP7 CASP8 CFLAR DAXX DFFA DFFB FADD FAF1 JUN LMNA LMNB1 LMNB2 MAP2K4 MAP3K1 MAP3K7 MAPK8 PAK1 PAK2 PRKDC PTPN13 RB1 RIPK2 SPTAN1 TNFRSF6 TNFSF6
G14 A2M APBB1 APH1A APOE APP BACE1 BACE2 C1QA C1QB C1QC CASP3 CASP7 GAPDH GSK3B HSD17B10 IDE IL1B LPL LRP1 MAPT MME NAE1 NCSTN PSEN1 PSEN2 PSENEN SNCA TNF
G15 ADPRT ARHGDIB BAG4 CASP2 CASP3 CASP8 CRADD DFFA DFFB FADD JUN LMNA LMNB1 LMNB2 MADD MAP2K4 MAP3K1 MAP3K7 MAPK8 PAK1 PAK2 PRKDC RB1 RIPK1 SPTAN1 TNF TNFRSF1A TRADD TRAF2
G16 ATN1 BAIAP2 CASP1 CASP3 CASP7 CASP8 GAPDH INS INSR ITCH MAGI1 MAGI2 RERE WWP1 WWP2
G17 AKT1 BAD CASP9 CHUK FOXO1A FOXO3A GH1 GHR HSPCA MLLT7 NFKB1 NFKBIA PDPK1 PIK3CA PIK3R1 PPP2CA RELA TNFSF6 YWHAH
G18 ARAF1 ATF1 BAD BRAF COPEB CREB1 CREB3 CREB5 DUSP4 DUSP6 DUSP9 EEF2K EIF4E GRB2 HTATIP MAP2K1 MAP2K2 MAP3K8 MAPK1 MAPK3 MKNK1 MKNK2 MOS NFKB1 RAP1A RPS6KA1 RPS6KA2 RPS6KA3 SHC1 SOS1 SOS2 TRAF3
G19 ABL1 CDKN2A E2F1 MDM2 MYC PIK3CA PIK3R1 POLR1A POLR1B POLR1C POLR1D RAC1 RB1 TBX2 TP53 TWIST1
G20 AKR1B1 ALDOA ALDOB ALDOC FBP1 FBP2 FPGT GCK GMDS GMPPA GMPPB HK1 HK2 HK3 KHK MPI PFKFB1 PFKFB3 PFKFB4 PFKM PFKP PMM1 PMM2 SORD TPI1
G21 AKT1 AKT2 AKT3 BCR BTK CD19 CDKN2A DAPP1 FLOT1 FLOT2 FOXO3A GAB1 ITPR1 ITPR2 ITPR3 LYN NR0B2 P101- PI3K PDK1 PHF11 PIK3CA PITX2 PLCG2 PPP1R13B PREX1 PSCD3 PTEN PTPRC RPS6KA1 RPS6KA2 RPS6KA3 RPS6KB1 SAG SYK TEC VAV1 G22 BRAF CCDC6 CCND1 CDH1 CTNNB1 HRAS KRAS LEF1 MAP2K1 MAP2K2 MAPK1 MAPK3 MYC NCOA4 NRAS NTRK1 PAX8 PPARG RET RXRA RXRB RXRG TCF7 TCF7L1 TCF7L2 TFG TP53 TPM3 TPR
G23 ABL1 ATM BRCA1 CDKN1A CHEK1 CHEK2 GADD45A JUN MAPK8 MDM2 MRE11A NBS1 NFKB1 NFKBIA RAD50 RAD51 RBBP8 RELA TP53 TP73
G24 AOX1 BST1 C9orf95 CD38 ENPP1 ENPP3 NADK NADSYN1 NMNAT1 NMNAT2 NMNAT3 NNMT NNT NP NT5C NT5C1A NT5C1B NT5C2 NT5C3 NT5E NT5M NUDT12 PBEF1 QPRT
G25 BAX BDNF CALM1 CALM2 CALM3 CALML3 CALML6 CASP1 CASP3 CASP6 CASP8 CBS CLTA CLTB CLTC CLTCL1 CREBBP DCTN1 EP300 GAPDH GRB2 HAP1 HIP1 HTT IFT57 NCOR1 PLEKHA8 RASA1 TGM2 TP53 UBE2K
G26 ASK CDC45L CDC6 CDC7 CDK2 CDT1 DIAPH2 GMNN MCM10 MCM2 MCM3 MCM4 MCM5 MCM6 MCM7 NACA NACA_/// _FKSG17 ORC1L ORC2L ORC3L ORC4L ORC5L ORC6L PCNA POLA POLA2 POLD1 POLD2 POLD3 POLD4 POLE POLE2 PRIM1 PRIM2A RFC1 RFC2 RFC3 RFC4 RFC5 RPA1 RPA2 RPA3 RPA4 RPS27A RPS27A_///_LOC388720_///_LOC389425 UBA52 UBB UBC G27 AKT1 BCL2 EGFR G22P1 HSPCA IGF1R KRAS2 MYC POLR2A PPP2CA PRKCA RB1 TEP1 TERF1 TERT TNKS TP53 XRCC5 G28 CHUK DUSP1 IKBKAP IKBKB IKBKG LTA MAP3K1 MAP3K14 NFKB1 NFKBIA RELA RIPK1 TANK TNFAIP3 TNFRSF1B TRAF1 TRAF2 TRAF3
G29 BCL2 CREBBP EP300 FYN IL2RG IL7 IL7R JAK1 JAK3 LCK NMI PIK3CA PIK3R1 PTK2B STAT5A STAT5B
G30 COL4A1 COL4A2 COL4A3 COL4A4 COL4A5 COL4A6 F10 F11 F12 F2 F2R F5 F8 F9 FGA FGB FGG KLKB1 KNG PROC PROS1 SERPINC1 SERPING1 Table S3a ClickTable.htm here to download Table: Table S3a.pdf 2/24/11 3:45 PM
Table S3a. Canonical pathways associated with normal samples in GSAAzs-ks (glioblastoma) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 NOS1PATHWAY 21 0.001233553 0.0127228 0.015 G2 PGC1APATHWAY 23 0 0.022594186 0.0133 G3 NDKDYNAMINPATHWAY 17 0.013639059 0.04568562 0.1725 G4 ST_GA12_PATHWAY 21 0.000601323 0.04634724 0.1978 G5 HSA04720_LONG_TERM_POTENTIATION 66 0.00022482 0.050192747 0.1635 G6 MEF2DPATHWAY 17 0.00901784 0.05373334 0.2766 G7 NKCELLSPATHWAY 17 0.00076365 0.054087915 0.0911 G8 TYPE_III_SECRETION_SYSTEM 18 0.028360749 0.054313727 0.3712 G9 CDMACPATHWAY 16 0.004357711 0.054838073 0.2564 G10 FCER1PATHWAY 37 0.000610625 0.055069838 0.4356 G11 CXCR4PATHWAY 23 0.001791045 0.055689923 0.4208 G12 CCR5PATHWAY 17 0.008371537 0.057200976 0.4089 G13 CALCINEURINPATHWAY 18 0.001370668 0.057563998 0.1574 G14 FLAGELLAR_ASSEMBLY 18 0.028360749 0.0584917 0.3712 G15 HSA04730_LONG_TERM_DEPRESSION 73 0 0.059360046 0.4965 G16 PYK2PATHWAY 27 0.003740648 0.061897844 0.5271 G17 FMLPPATHWAY 34 0.002518363 0.062080692 0.4939 G18 PHOTOSYNTHESIS 19 0.033769682 0.062189028 0.5792 G19 ATP_SYNTHESIS 18 0.028360749 0.06336601 0.3712 G20 AT1RPATHWAY 34 0.000839631 0.06347621 0.3455 G21 CCR3PATHWAY 22 0.003056235 0.06491319 0.5788 G22 ST_WNT_CA2_CYCLIC_GMP_PATHWAY 19 0.000609632 0.06595326 0.1449 G23 HSA04740_OLFACTORY_TRANSDUCTION 28 0.002124044 0.06700691 0.5727 G24 BCRPATHWAY 34 0.002636382 0.0739493 0.6556 G25 VIPPATHWAY 25 0.015846882 0.08727022 0.7244 G26 KERATINOCYTEPATHWAY 43 0.000398883 0.08910543 0.7603 G27 HSA05120_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTION 61 0.00081367 0.09235378 0.7597 G28 NO1PATHWAY 27 0.008421052 0.09824378 0.8141 G29 HSA04320_DORSO_VENTRAL_AXIS_FORMATION 23 0.016485576 0.09914897 0.8259 G30 G_PROTEIN_SIGNALING 85 0.000667854 0.10141361 0.8129 G31 HSA04916_MELANOGENESIS 90 0.000214684 0.10897859 0.8625 G32 ST_ADRENERGIC 33 0.004924168 0.11755399 0.887 G33 ERK5PATHWAY 17 0.036797337 0.11863474 0.9267 G34 SA_B_CELL_RECEPTOR_COMPLEXES 24 0.027027028 0.119093135 0.9389 G35 HSA00562_INOSITOL_PHOSPHATE_METABOLISM 40 0.005077216 0.12020793 0.9325 G36 ST_MYOCYTE_AD_PATHWAY 24 0.011623402 0.120392755 0.9026 G37 BIOPEPTIDESPATHWAY 38 0.008541533 0.12062802 0.8984 G38 HSA04930_TYPE_II_DIABETES_MELLITUS 40 0.004790669 0.12079803 0.9376 G39 HSA04540_GAP_JUNCTION 85 0.000221631 0.12084239 0.9255 G40 GPCRPATHWAY 33 0.023541667 0.121453024 0.9211 G41 PAR1PATHWAY 19 0.04069196 0.121750236 0.9454 G42 HSA04070_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 67 0.000648929 0.1222293 0.911 G43 HDACPATHWAY 29 0.014242555 0.12455851 0.9208 G44 HSA00534_HEPARAN_SULFATE_BIOSYNTHESIS 16 0.06652191 0.12477932 0.952 G45 EIF4PATHWAY 24 0.025395585 0.12511018 0.9555 G46 CREBPATHWAY 26 0.029504742 0.13420863 0.9715 G47 HSA05110_CHOLERA_INFECTION 36 0.025270022 0.13421041 0.9644 G48 INOSITOL_PHOSPHATE_METABOLISM 22 0.03858521 0.13586749 0.9708 G49 HSA04912_GNRH_SIGNALING_PATHWAY 92 0.000863558 0.13591036 0.9683 G50 NFATPATHWAY 50 0.007166124 0.1362463 0.9733 G51 IGF1RPATHWAY 15 0.07441182 0.14259791 0.979 G52 PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 85 0.001952278 0.14739046 0.9838 G53 GCRPATHWAY 17 0.06315577 0.14746554 0.983 G54 ST_G_ALPHA_I_PATHWAY 34 0.018344799 0.14753346 0.9847
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 3:45 PM
G55 TCRPATHWAY 42 0.021489972 0.15234596 0.9873 G56 ST_INTEGRIN_SIGNALING_PATHWAY 75 0.003269978 0.15467903 0.9891 G57 MAPKPATHWAY 84 0.002659574 0.15634264 0.9888 G58 HSA05030_AMYOTROPHIC_LATERAL_SCLEROSIS 17 0.083501 0.17749725 0.996 G59 METPATHWAY 33 0.029076621 0.17961368 0.996 G60 GLUTAMATE_METABOLISM 22 0.07129836 0.17983755 0.9958 G61 SIG_BCR_SIGNALING_PATHWAY 44 0.029166667 0.18095538 0.9957 G62 HSA04012_ERBB_SIGNALING_PATHWAY 84 0.006393862 0.18733314 0.9972 G63 HSA04520_ADHERENS_JUNCTION 72 0.010257442 0.20039909 0.998 G64 ST_GRANULE_CELL_SURVIVAL_PATHWAY 27 0.04684359 0.20295797 0.9982 G65 PHENYLALANINE_METABOLISM 20 0.09293824 0.22702353 0.9991 G66 MONOAMINE_GPCRS 28 0.10088715 0.23300084 0.9993 G67 ST_JNK_MAPK_PATHWAY 40 0.034070168 0.23363066 0.9993 G68 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS 43 0.03351042 0.2411943 0.9993 G69 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_CHEMOTAXIS_PATHWAY 30 0.06785137 0.24120751 0.9993 G70 SA_PTEN_PATHWAY 17 0.1298676 0.24166472 0.9993 G71 HSA04664_FC_EPSILON_RI_SIGNALING_PATHWAY 73 0.024772096 0.24453779 0.9993 G72 ST_GA13_PATHWAY 35 0.047883965 0.25054777 0.9995 G73 EGFPATHWAY 27 0.0812794 0.25165054 0.9996 G74 ERKPATHWAY 30 0.064084075 0.2526748 0.9996 G75 ST_B_CELL_ANTIGEN_RECEPTOR 39 0.06341463 0.25454217 0.9996 G76 EDG1PATHWAY 25 0.08813422 0.25803098 0.9997 G77 CK1PATHWAY 15 0.19817315 0.25826213 0.9997 G78 HSA05214_GLIOMA 62 0.02879039 0.25989217 0.9997 G79 PTDINSPATHWAY 20 0.12973079 0.2682453 0.9998 G80 GLEEVECPATHWAY 22 0.12194204 0.2813196 0.9998 G81 SIG_CD40PATHWAYMAP 33 0.080066726 0.28357813 0.9999 G82 IL2PATHWAY 22 0.15662411 0.28546396 0.9999 G83 SIG_CHEMOTAXIS 42 0.060815047 0.29727653 1 G84 ST_GAQ_PATHWAY 27 0.10731132 0.29805934 1 G85 INSULINPATHWAY 21 0.14232558 0.31100434 1 G86 NGFPATHWAY 19 0.17059378 0.31697896 1 G87 PDGFPATHWAY 27 0.13182601 0.31715435 1 G88 CARBON_FIXATION 19 0.19961014 0.32422864 1 G89 HSA05218_MELANOMA 68 0.04736505 0.32744646 1 G90 SIG_REGULATION_OF_THE_ACTIN_CYTOSKELETON_BY_RHO_GTPASES 33 0.15177833 0.35101092 1 G91 HSA00960_ALKALOID_BIOSYNTHESIS_II 15 0.2646229 0.35265166 1 G92 SIG_PIP3_SIGNALING_IN_CARDIAC_MYOCTES 64 0.06595253 0.353991 1 G93 HSA01510_NEURODEGENERATIVE_DISEASES 35 0.13150743 0.355101 1 G94 TPOPATHWAY 23 0.16426677 0.35583097 1 G95 PTENPATHWAY 16 0.26301268 0.3569682 1 G96 HSA04370_VEGF_SIGNALING_PATHWAY 66 0.0688755 0.35709023 1 G97 GHPATHWAY 27 0.13627255 0.35808477 1 G98 ST_T_CELL_SIGNAL_TRANSDUCTION 42 0.13088894 0.37233877 1 G99 HSA00251_GLUTAMATE_METABOLISM 27 0.2111042 0.37276357 1 G100 WNT_SIGNALING 58 0.10035248 0.38533178 1 G101 HSA04660_T_CELL_RECEPTOR_SIGNALING_PATHWAY 90 0.09014084 0.38786605 1 G102 IGF1PATHWAY 20 0.23003374 0.39342383 1 G103 GLYCOLYSIS_AND_GLUCONEOGENESIS 42 0.19271776 0.441113 1 G104 ARGININE_AND_PROLINE_METABOLISM 40 0.1842786 0.44877797 1 G105 HSA04920_ADIPOCYTOKINE_SIGNALING_PATHWAY 68 0.13929147 0.45106035 1 G106 P38MAPKPATHWAY 39 0.19898786 0.46023792 1 G107 GPCRDB_OTHER 47 0.20801954 0.465733 1 G108 HSA00710_CARBON_FIXATION 21 0.32489365 0.46897388 1 G109 SIG_INSULIN_RECEPTOR_PATHWAY_IN_CARDIAC_MYOCYTES 50 0.1801714 0.46968266 1 G110 BETA_ALANINE_METABOLISM 25 0.29040655 0.47074002 1 G111 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY 33 0.22693218 0.47086 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 3:45 PM
G112 GLYCEROPHOSPHOLIPID_METABOLISM 45 0.19535354 0.47132447 1 G113 ACTINYPATHWAY 16 0.3444912 0.4713816 1 G114 HSA04742_TASTE_TRANSDUCTION 34 0.2366801 0.4739702 1 G115 HSA00910_NITROGEN_METABOLISM 23 0.3077079 0.47411004 1 G116 HSA05211_RENAL_CELL_CARCINOMA 67 0.15114823 0.47444946 1 G117 PROPANOATE_METABOLISM 29 0.25849515 0.4768045 1 G118 HSA00410_BETA_ALANINE_METABOLISM 24 0.30957147 0.47702578 1 G119 HSA00330_ARGININE_AND_PROLINE_METABOLISM 29 0.27940887 0.48082817 1 G120 HSA00020_CITRATE_CYCLE 23 0.34247947 0.5043129 1 G121 HSA00564_GLYCEROPHOSPHOLIPID_METABOLISM 55 0.23497267 0.50615495 1 G122 HSA04130_SNARE_INTERACTIONS_IN_VESICULAR_TRANSPORT 30 0.3220748 0.51616234 1 G123 RAC1PATHWAY 22 0.3678777 0.5200105 1 G124 HSA03320_PPAR_SIGNALING_PATHWAY 59 0.25919732 0.5235906 1 G125 TRYPTOPHAN_METABOLISM 51 0.27628115 0.5255228 1 G126 HSA00380_TRYPTOPHAN_METABOLISM 49 0.27436003 0.5263677 1 G127 HSA00350_TYROSINE_METABOLISM 48 0.27458677 0.5290026 1 G128 BUTANOATE_METABOLISM 26 0.3497814 0.53033113 1 G129 ETSPATHWAY 15 0.4389881 0.53704494 1 G130 HSA00602_GLYCOSPHINGOLIPID_BIOSYNTHESIS_NEO_LACTOSERIES 20 0.40822968 0.5453535 1 G131 GPCRDB_CLASS_B_SECRETIN_LIKE 22 0.3970023 0.5460234 1 G132 HSA04150_MTOR_SIGNALING_PATHWAY 44 0.3370479 0.54721355 1 G133 EPOPATHWAY 19 0.41470364 0.54781127 1 G134 HISTIDINE_METABOLISM 23 0.39686322 0.5496829 1 G135 ALANINE_AND_ASPARTATE_METABOLISM 18 0.46440747 0.57397854 1 G136 TYROSINE_METABOLISM 27 0.41031745 0.5740127 1 G137 CALCINEURIN_NF_AT_SIGNALING 90 0.31490046 0.5751543 1 G138 HSA00360_PHENYLALANINE_METABOLISM 26 0.41701534 0.57536805 1 G139 NITROGEN_METABOLISM 20 0.45374095 0.5790585 1 G140 PENTOSE_PHOSPHATE_PATHWAY 22 0.44515753 0.579184 1 G141 GLYCEROLIPID_METABOLISM 39 0.38216174 0.58114153 1 G142 HSA00640_PROPANOATE_METABOLISM 29 0.44174367 0.59663445 1 G143 HSA01031_GLYCAN_STRUCTURES_BIOSYNTHESIS_2 53 0.38991416 0.5994672 1 G144 HSA00340_HISTIDINE_METABOLISM 33 0.4361935 0.6004784 1 G145 HSA00650_BUTANOATE_METABOLISM 40 0.41470528 0.6031486 1 G146 HSA00561_GLYCEROLIPID_METABOLISM 48 0.41701785 0.6035628 1 G147 SA_TRKA_RECEPTOR 16 0.50812024 0.6089215 1 G148 PPARAPATHWAY 51 0.42516938 0.61023545 1 G149 HSA00600_SPHINGOLIPID_METABOLISM 29 0.46767068 0.61412734 1 G150 MPRPATHWAY 22 0.5101709 0.625135 1 G151 GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 26 0.5096991 0.62618107 1 G152 HSA00620_PYRUVATE_METABOLISM 36 0.4960532 0.6460283 1 G153 SIG_IL4RECEPTOR_IN_B_LYPHOCYTES 27 0.518899 0.6464538 1 G154 GLYCOLYSIS 48 0.528317 0.67855453 1 G155 GLUCONEOGENESIS 48 0.528317 0.6829323 1 G156 IL12PATHWAY 19 0.5797101 0.68723303 1 G157 BADPATHWAY 21 0.5610687 0.6873498 1 G158 RHOPATHWAY 29 0.57734203 0.70395625 1 G159 CITRATE_CYCLE_TCA_CYCLE 19 0.6182806 0.70646375 1 G160 NUCLEAR_RECEPTORS 38 0.5832171 0.70683664 1 G161 HSA00010_GLYCOLYSIS_AND_GLUCONEOGENESIS 55 0.6100731 0.71052694 1 G162 PEPTIDE_GPCRS 68 0.60441566 0.7106164 1 G163 ANDROGEN_AND_ESTROGEN_METABOLISM 22 0.60015005 0.71075606 1 G164 HSA00252_ALANINE_AND_ASPARTATE_METABOLISM 28 0.60661227 0.71100545 1 G165 HSA00980_METABOLISM_OF_XENOBIOTICS_BY_CYTOCHROME_P450 50 0.58123714 0.7112832 1 G166 CIRCADIAN_EXERCISE 39 0.6176292 0.7139626 1 G167 OXIDATIVE_PHOSPHORYLATION 54 0.57273465 0.71836454 1 G168 HSA00150_ANDROGEN_AND_ESTROGEN_METABOLISM 40 0.65870035 0.7450198 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 3:45 PM
G169 HSA04340_HEDGEHOG_SIGNALING_PATHWAY 45 0.6681214 0.75208306 1 G170 PYRUVATE_METABOLISM 34 0.66784084 0.7585629 1 G171 CHREBPPATHWAY 16 0.6796396 0.76024127 1 G172 ST_WNT_BETA_CATENIN_PATHWAY 28 0.71818787 0.7852281 1 G173 HSA04140_REGULATION_OF_AUTOPHAGY 28 0.6729584 0.78624505 1 G174 NO2IL12PATHWAY 15 0.6878931 0.79976207 1 G175 VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 34 0.7352289 0.8022026 1 G176 WNTPATHWAY 25 0.7298729 0.80320704 1 G177 STRIATED_MUSCLE_CONTRACTION 33 0.7576864 0.8066459 1 G178 HSA00280_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 42 0.8085755 0.85786957 1 G179 KREBS_TCA_CYCLE 26 0.8085914 0.8782068 1 G180 UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS 16 0.8024247 0.89618844 1 G181 BILE_ACID_BIOSYNTHESIS 23 0.8706329 0.9347252 1 G182 HSA00190_OXIDATIVE_PHOSPHORYLATION 98 0.96245736 0.982899 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S3b ClickTable.htm here to download Table: Table S3b.pdf 2/24/11 3:48 PM
Table S3b. Canonical pathways associated with normal samples in GSAAzs-ks (glioblastoma) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 BIOCARTA_NOS1_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NOS1_PATHWAY.html G2 BIOCARTA_PGC1A_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_PGC1A_PATHWAY.html G3 BIOCARTA_NDKDYNAMIN_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NDKDYNAMIN_PATHWAY.html G4 ST_GA12_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_GA12_PATHWAY.html G5 KEGG_LONG_TERM_POTENTIATION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_LONG_TERM_POTENTIATION.html G6 BIOCARTA_MEF2D_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_MEF2D_PATHWAY.html G7 BIOCARTA_NKCELLS_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NKCELLS_PATHWAY.html G8 N/A N/A G9 BIOCARTA_CDMAC_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CDMAC_PATHWAY.html G10 BIOCARTA_FCER1_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_FCER1_PATHWAY.html G11 BIOCARTA_CXCR4_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CXCR4_PATHWAY.html G12 BIOCARTA_CCR5_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CCR5_PATHWAY.html G13 BIOCARTA_CALCINEURIN_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CALCINEURIN_PATHWAY.html G14 N/A N/A G15 KEGG_LONG_TERM_DEPRESSION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_LONG_TERM_DEPRESSION.html G16 BIOCARTA_PYK2_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_PYK2_PATHWAY.html G17 BIOCARTA_FMLP_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_FMLP_PATHWAY.html G18 N/A N/A G19 N/A N/A G20 BIOCARTA_AT1R_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_AT1R_PATHWAY.html G21 BIOCARTA_CCR3_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CCR3_PATHWAY.html G22 ST_WNT_CA2_CYCLIC_GMP_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_WNT_CA2_CYCLIC_GMP_PATHWAY.html G23 KEGG_OLFACTORY_TRANSDUCTION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_OLFACTORY_TRANSDUCTION.html G24 BIOCARTA_BCR_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_BCR_PATHWAY.html G25 BIOCARTA_VIP_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_VIP_PATHWAY.html G26 BIOCARTA_KERATINOCYTE_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_KERATINOCYTE_PATHWAY.html G27 KEGG_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTIONhttp://www.broadinstitute.org/gsea/msigdb/cards/KEGG_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTION.html G28 BIOCARTA_NO1_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NO1_PATHWAY.html G29 KEGG_DORSO_VENTRAL_AXIS_FORMATION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_DORSO_VENTRAL_AXIS_FORMATION.html G30 N/A N/A G31 KEGG_MELANOGENESIS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_MELANOGENESIS.html G32 ST_ADRENERGIC http://www.broadinstitute.org/gsea/msigdb/cards/ST_ADRENERGIC.html G33 BIOCARTA_ERK5_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_ERK5_PATHWAY.html G34 SA_B_CELL_RECEPTOR_COMPLEXES http://www.broadinstitute.org/gsea/msigdb/cards/SA_B_CELL_RECEPTOR_COMPLEXES.html G35 KEGG_INOSITOL_PHOSPHATE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_INOSITOL_PHOSPHATE_METABOLISM.html G36 ST_MYOCYTE_AD_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_MYOCYTE_AD_PATHWAY.html G37 BIOCARTA_BIOPEPTIDES_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_BIOPEPTIDES_PATHWAY.html G38 KEGG_TYPE_II_DIABETES_MELLITUS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_TYPE_II_DIABETES_MELLITUS.html G39 KEGG_GAP_JUNCTION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GAP_JUNCTION.html G40 BIOCARTA_GPCR_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_GPCR_PATHWAY.html G41 BIOCARTA_PAR1_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_PAR1_PATHWAY.html G42 KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM.html G43 BIOCARTA_HDAC_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_HDAC_PATHWAY.html G44 KEGG_GLYCOSAMINOGLYCAN_BIOSYNTHESIS_HEPARAN_SULFATE http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GLYCOSAMINOGLYCAN_BIOSYNTHESIS_HEPARAN_SULFATE.html G45 BIOCARTA_EIF4_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_EIF4_PATHWAY.html G46 BIOCARTA_CREB_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CREB_PATHWAY.html G47 KEGG_VIBRIO_CHOLERAE_INFECTION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_VIBRIO_CHOLERAE_INFECTION.html G48 N/A N/A G49 KEGG_GNRH_SIGNALING_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GNRH_SIGNALING_PATHWAY.html G50 BIOCARTA_NFAT_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NFAT_PATHWAY.html G51 BIOCARTA_IGF1R_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_IGF1R_PATHWAY.html G52 KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM.html G53 BIOCARTA_GCR_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_GCR_PATHWAY.html G54 ST_G_ALPHA_I_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_G_ALPHA_I_PATHWAY.html G55 BIOCARTA_TCR_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_TCR_PATHWAY.html G56 ST_INTEGRIN_SIGNALING_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_INTEGRIN_SIGNALING_PATHWAY.html G57 BIOCARTA_MAPK_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_MAPK_PATHWAY.html G58 KEGG_AMYOTROPHIC_LATERAL_SCLEROSIS_ALS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_AMYOTROPHIC_LATERAL_SCLEROSIS_ALS.html G59 BIOCARTA_MET_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_MET_PATHWAY.html G60 N/A N/A G61 SIG_BCR_SIGNALING_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/SIG_BCR_SIGNALING_PATHWAY.html G62 KEGG_ERBB_SIGNALING_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_ERBB_SIGNALING_PATHWAY.html G63 KEGG_ADHERENS_JUNCTION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_ADHERENS_JUNCTION.html G64 ST_GRANULE_CELL_SURVIVAL_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_GRANULE_CELL_SURVIVAL_PATHWAY.html G65 KEGG_PHENYLALANINE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PHENYLALANINE_METABOLISM.html G66 N/A N/A G67 ST_JNK_MAPK_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_JNK_MAPK_PATHWAY.html G68 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS http://www.broadinstitute.org/gsea/msigdb/cards/ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS.html G69 N/A N/A G70 SA_PTEN_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/SA_PTEN_PATHWAY.html G71 KEGG_FC_EPSILON_RI_SIGNALING_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_FC_EPSILON_RI_SIGNALING_PATHWAY.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S3c ClickTable.htm here to download Table: Table S3c.pdf 2/24/11 3:51 PM
Table S3c. Canonical pathways associated with normal samples in GSAAzs-ks (glioblastoma) Sorted by FDR Index Description G1 Glutamate stimulates NMDA-mediates calcium influx, which promotes nitric oxide synthesis from arginine by neuronal nitric oxide synthase, activating guanylate cyclase. G2 PCG-1a is expressed in skeletal muscle, heart muscle, and brown fat, and is a coactivator for receptors such as glucocorticoid receptor and thyroid hormone receptor. G3 Endocytotic role of NDK, Phosphins and Dynamin G4 G-alpha-12 promotes cell survival and proliferation, is involved in the stress response, and activates JNK. G5 Genes involved in long-term potentiation G6 Mef2 transcription factors promote calcium-induced apoptosis in T cells and are regulated by MAP kinases and histone deacetylases. G7 Natural killer (NK) lymphocytes are inhibited by MHC and activated by surface glycoproteins on tumor or virus-infected cells, which undergo perforin-mediated lysis. G8 N/A G9 Cadmium 2+ promotes cell proliferation in cultured macrophages by entering the cell via calcium channels and activating the MAP kinase pathway. G10 In mast cells, Fc epsilon receptor 1 activates BTK, PKC, and the MAP kinase pathway to promote degranulation and arachnidonic acid release. G11 CXCR4 is a G-protein coupled receptor that responds to the ligand SDF-1 by activating Ras and PI3 kinase to promote lymphocyte chemotaxis. G12 CCR5 is a G-protein coupled receptor expressed in macrophages that recognizes chemokine ligands and is targeted by the HIV envelope protein GP120. G13 Increased intracellular calcium activates the phosphatase calcineurin in differentiating keratinocytes. G14 N/A G15 Genes involved in long-term depression G16 Pyk2 and Rac1 stimulate the JNK cascade and activate MKK3, which activates p38. G17 The fMLP receptor is a G-protein coupled receptor in neutrophils that recognizes formylated bacterial peptides and activates NADPH oxidase. G18 N/A G19 N/A G20 Binding of angiotensin II to AT1-R activates Ca2+ signaling and the JNK pathway. G21 CCR3 is a G-protein coupled receptor that recruits eosinophils to inflammation sites via chemokine ligands. G22 Some Wnt glycoprotein/Frizzled receptor interactions increase intracellular calcium and decrease cGMP. G23 Genes involved in olfactory transduction G24 B cell antigen receptors (BCRs) activate tyrosine kinases and transiently increase tyrosine phosphorylation on binding to antigen. G25 Apoptosis of activated T cells is inhibited by vasoactive intestinal peptide (VIP) and its relative PACAP. G26 Keratinocyte differentiation, which models the differentiation of epidermal cells, requires the four main MAP kinase pathways. G27 Genes involved in epithelial cell signaling in Helicobacter pylori infection G28 Shear stress in endothelial cells increases cytoplasmic calcium, which activates nitric oxide synthase III to release NO, which in turn regulates cardiac contractions. G29 Genes involved in dorso-ventral axis formation G30 N/A G31 Genes involved in melanogenesis G32 Adrenergic receptors respond to epinephrine and norepinephrine signaling. G33 Signaling between a tissue and its innervating axon stimulates retrograde transport via Trk receptors, which activate Erk5, which induces transcription of anti-apoptotic factors. G34 Antigen binding to B cell receptors activates protein tyrosine kinases, such as the Src family, which ultimate activate MAP kinases. G35 Genes involved in inositol phosphate metabolism G36 Cardiac myocytes have a variety of adrenergic receptors that induce subtype-specific signaling effects. G37 Extracellular signaling peptides exert biological effects via G-protein coupled receptors (GPCRs), which activate intracellular GTPases. G38 Genes involved in type II diabetes mellitus G39 Genes involved in gap junction G40 G-protein coupled receptors activate adenylyl cyclase, which converts ATP to cAMP, to activate second messenger pathways. G41 Activated extracellular thrombin cleaves and activates the G-protein coupled receptors PAR1 and PAR4, which activate platelets. G42 Genes involved in phosphatidylinositol signaling system G43 Myocyte enhancer factor MEF2 activates transcription of genes required for muscle cell differentiation and is inhibited by histone deacetylases. G44 Genes involved in heparan sulfate biosynthesis G45 The eIF-4F complex recognizes 5' mRNA caps, recruits RNA helicases, and maintains mRNA-ribosome bridging. G46 CREB is a transcription factor that binds to cAMP-responsive elements (CREs) to activate transcription in response to extracellular signaling. G47 Genes involved in cholera - infection G48 N/A G49 Genes involved in GnRH signaling pathway G50 Cardiac hypertrophy is induced by NF-ATc4 and GATA4, which are stimulated through calcineurin activated by CaMK. G51 Insulin-like growth factor receptor IGF-1R promotes cell growth and inhibits apoptosis on binding of ligands IGF-1 and 2 via Ras activation and the AKT pathway. G52 Genes involved in phosphatidylinositol signaling system G53 Corticosteroids activate the glucocorticoid receptor (GR), which inhibits NF-kB and activates Annexin-1, thus inhibiting the inflammatory response. G54 Gi and Go proteins are members of the same family that transduce cellular signals through both their alpha and beta subunits. G55 T cell receptors bind to foreign peptides presented by MHC molecules and induce T cell activation. G56 Integrins are transmembrane receptors that mediate cell growth, survival, and migration by binding to ligands in the extracellular matrix. G57 The mitogen-activated protein (MAP) kinase pathway is a common signaling mechanism and has four main sub-pathways: Erk, JNK/SAPK, p53, and ERK5. G58 Genes involved in amyotrophic lateral sclerosis (ALS) G59 The hepatocyte growth factor receptor c-Met stimulates proliferation and alters cell motility and adhesion on binding the ligand HGF. G60 N/A G61 Members of the BCR signaling pathway G62 Genes involved in ErbB signaling pathway G63 Genes involved in adherens junction G64 The survival and differentiation of granule cells in the brain is controlled by pro-growth PACAP and pro-apoptotic ceramides. G65 G66 N/A G67 JNKs are MAP kinases regulated by several levels of kinases (MAPKK, MAPKKK) and phosphorylate transcription factors and regulatory proteins. G68 Rat-derived PC12 cells respond to nerve growth factor (NGF) and PACAP to differentiate into neuronal cells. G69 The fungus Dictyostelium discoideum is a model system for cytoskeletal organization during chemotaxis. G70 PTEN is a tumor suppressor that dephosphorylates the lipid messenger phosphatidylinositol triphosphate. G71 Genes involved in Fc epsilon RI signaling pathway
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S3d Click here to download Table: Table S3d.pdf
Table S3d. Canonical pathways associated with normal samples in GSAAzs-ks (glioblastoma)
Sorted by FDR
Index Genes
G1 CALM1 CALM2 CALM3 DLG4 GRIN1 GRIN2A GRIN2B GRIN2C GRIN2D NOS1 PPP3CA PPP3CB PPP3CC PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 SYT1
G2 CALM1 CALM2 CALM3 CAMK1 CAMK1G CAMK2A CAMK2B CAMK2D CAMK2G CAMK4 ESRRA HDAC5 MEF2A MEF2B MEF2C MEF2D PPARA PPARGC1 PPP3CA PPP3CB PPP3CC SLC2A4 SYT1 YWHAH
G3 AMPH AP2A1 AP2M1 BIN1 CALM1 CALM2 CALM3 DNM1 EPN1 EPS15 NME1 NME2 PICALM PPP3CA PPP3CB PPP3CC SYNJ1 SYNJ2 SYT1
G4 BF BTK DLG4 EPHB2 F2 F2RL1 F2RL2 F2RL3 JUN MAP2K5 MAPK1 MAPK7 MAPK8 MYEF2 PLD1 PLD2 PLD3 PTK2 RAF1 RASAL1 SRC TEC VAV1
G5 ADCY1 ADCY8 ARAF ATF4 BRAF CACNA1C CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CAMK4 CHP CREBBP EP300 GNAQ GRIA1 GRIA2 GRIN1 GRIN2A GRIN2B GRIN2C GRIN2D GRM1 GRM5 HRAS ITPR1 ITPR2 ITPR3 KRAS MAP2K1 MAP2K2 MAPK1 MAPK3 NRAS PLCB1 PLCB2 PLCB3 PLCB4 PPP1CA PPP1CB PPP1CC PPP1R12A PPP1R1A PPP3CA PPP3CB PPP3CC PPP3R1 PPP3R2 PRKACA PRKACB PRKACG PRKCA PRKCB1 PRKCG PRKX PRKY RAF1 RAP1A RAP1B RAPGEF3 RPS6KA1 RPS6KA2 RPS6KA3 RPS6KA6
G6 CABIN1 CALM1 CALM2 CALM3 CAPN2 CAPNS1 CAPNS2 EP300 HDAC1 HDAC2 MEF2D NFATC1 NFATC2 PPP3CA PPP3CB PPP3CC PRKCA PRKCB1 SYT1 TRA@ TRB@
G7 B2M HLA-A IL18 ITGB1 KLRC1 KLRC2 KLRC3 KLRC4 KLRD1 LAT MAP2K1 MAPK3 PAK1 PIK3CA PIK3R1 PTK2B PTPN6 RAC1 SYK VAV1
G8 ATP5E ATP5O ATP6AP1 ATP6V0A1 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0C /// SHMT1 ATP6V0D1 ATP6V0E ATP6V1A ATP6V1B1 ATP6V1B2 ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H
G9 CUZD1 FOS HRAS JUN MAP2K1 MAPK1 MAPK3 MYC NFKB1 NFKBIA PLCB1 PRKCA PRKCB1 RAF1 RELA TNF
G10 BTK CALM1 CALM2 CALM3 ELK1 FCER1A FCER1G FOS GRB2 HRAS JUN LYN MAP2K1 MAP2K4 MAP2K7 MAP3K1 MAPK1 MAPK3 MAPK8 NFATC1 NFATC2 NFATC3 NFATC4 PAK2 PIK3CA PIK3R1 PLA2G4A PLCG1 PPP3CA PPP3CB PPP3CC PRKCB1 RAF1 SHC1 SOS1 SYK SYT1 VAV1
G11 BCAR1 CRK CXCL12 CXCR4 GNAI1 GNAQ GNB1 GNGT1 HRAS MAP2K1 MAPK1 MAPK3 NFKB1 PIK3C2G PIK3CA PIK3R1 PLCG1 PRKCA PRKCB1 PTK2 PTK2B PXN RAF1 RELA
G12 CALM1 CALM2 CALM3 CCL2 CCL4 CCR5 CXCL12 CXCR4 FOS GNAQ JUN MAPK14 MAPK8 PLCG1 PRKCA PRKCB1 PTK2B SYT1
G13 CALM1 CALM2 CALM3 CDKN1A GNAQ MARCKS NFATC1 NFATC2 NFATC3 NFATC4 PLCG1 PPP3CA PPP3CB PPP3CC PRKCA PRKCB1 SP1 SP3 SYT1 G14 ATP5E ATP5O ATP6AP1 ATP6V0A1 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0C_///_SHMT1 ATP6V0D1 ATP6V0E ATP6V1A ATP6V1B1 ATP6V1B2 ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H
G15 ARAF BRAF C7orf16 CACNA1A CRH CRHR1 GNA11 GNA12 GNA13 GNAI1 GNAI2 GNAI3 GNAO1 GNAQ GNAS GNAZ GRIA1 GRIA2 GRIA3 GRID2 GRM1 GRM5 GUCY1A2 GUCY1A3 GUCY1B3 GUCY2C GUCY2D GUCY2F HRAS IGF1 IGF1R ITPR1 ITPR2 ITPR3 KRAS LYN MAP2K1 MAP2K2 MAPK1 MAPK3 NOS1 NOS2A NOS3 NPR1 NPR2 NRAS PLA2G10 PLA2G12A PLA2G12B PLA2G1B PLA2G2A PLA2G2D PLA2G2E PLA2G2F PLA2G3 PLA2G4A PLA2G5 PLA2G6 PLCB1 PLCB2 PLCB3 PLCB4 PPP2CA PPP2CB PPP2R1A PPP2R1B PPP2R2A PPP2R2B PPP2R2C PRKCA PRKCB1 PRKCG PRKG1 PRKG2 RAF1 RYR1
G16 BCAR1 CALM1 CALM2 CALM3 CRKL GNAQ GRB2 HRAS JUN MAP2K1 MAP2K2 MAP2K3 MAP2K4 MAP3K1 MAPK1 MAPK14 MAPK3 MAPK8 PAK1 PLCG1 PRKCA PRKCB1 PTK2B RAC1 RAF1 SHC1 SOS1 SRC SYT1
G17 CALM1 CALM2 CALM3 CAMK1 CAMK1G ELK1 FPR1 GNA15 GNB1 GNGT1 HRAS MAP2K1 MAP2K2 MAP2K3 MAP2K6 MAP3K1 MAPK1 MAPK14 MAPK3 NCF1 NCF2 NFATC1 NFATC2 NFATC3 NFATC4 NFKB1 NFKBIA PAK1 PIK3C2G PLCB1 PPP3CA PPP3CB PPP3CC RAC1 RAF1 RELA SYT1
G18 ATP5E ATP5O ATP6AP1 ATP6V0A1 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0C /// SHMT1 ATP6V0D1 ATP6V0E ATP6V1A ATP6V1B1 ATP6V1B2 ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H FDXR
G19 ATP5E ATP5O ATP6AP1 ATP6V0A1 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0C_///_SHMT1 ATP6V0D1 ATP6V0E ATP6V1A ATP6V1B1 ATP6V1B2 ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H
G20 AGT AGTR1 ATF2 CALM1 CALM2 CALM3 EGFR ELK1 GNAQ GRB2 HRAS JUN MAP2K1 MAP2K2 MAP2K4 MAP3K1 MAPK1 MAPK3 MAPK8 MEF2A MEF2B MEF2C MEF2D PAK1 PRKCA PRKCB1 PTK2 PTK2B RAC1 RAF1 SHC1 SOS1 SRC SYT1
G21 ARHA CCL11 CCR3 CFL1 GNAQ GNAS GNB1 GNGT1 HRAS LIMK1 MAP2K1 MAPK1 MAPK3 MYL2 NOX1 PIK3C2G PLCB1 PPP1R12B PRKCA PRKCB1 PTK2 RAF1 ROCK2
G22 BF CAMK2A CAMK2B CAMK2D CAMK2G DAG1 ITPKA ITPKB ITPR1 ITPR2 ITPR3 NFAT5 PDE6A PDE6B PDE6C PDE6D PDE6G PDE6H SLC6A13 TF
G23 ADCY3 ADRBK2 ARRB2 CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CLCA1 CLCA2 CLCA4 CNGA3 CNGA4 CNGB1 GNAL GUCA1A GUCA1B GUCA1C PDC PDE1C PRKACA PRKACB PRKACG PRKG1 PRKG2 PRKX PRKY
G24 BLNK BTK CALM1 CALM2 CALM3 CD79A CD79B ELK1 FOS GRB2 HRAS JUN LYN MAP2K1 MAP3K1 MAPK14 MAPK3 MAPK8 NFATC1 NFATC2 NFATC3 NFATC4 PLCG1 PPP3CA PPP3CB PPP3CC PRKCA PRKCB1 RAC1 RAF1 SHC1 SOS1 SYK SYT1 VAV1
G25 CALM1 CALM2 CALM3 CHUK EGR2 EGR3 GNAQ MAP3K1 MYC NFATC1 NFATC2 NFKB1 NFKBIA PLCG1 PPP3CA PPP3CB PPP3CC PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B RELA SYT1 VIP VIPR2
G26 BCL2 CEBPA CHUK DAXX EGF EGFR ETS1 ETS2 FOS HOXA7 HRAS IKBKB JUN MAP2K1 MAP2K3 MAP2K4 MAP2K6 MAP2K7 MAP3K1 MAP3K14 MAP3K5 MAPK1 MAPK13 MAPK14 MAPK3 MAPK8 NFKB1 NFKBIA PPP2CA PRKCA PRKCB1 PRKCD PRKCE PRKCG PRKCH PRKCQ RAF1 RELA RIPK1 SP1 TNF TNFRSF1A TNFRSF1B TNFRSF6 TNFSF6 TRAF2
G27 ADAM10 ADAM17 ATP6AP1 ATP6V0A1 ATP6V0A2 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0D1 ATP6V0D2 ATP6V0E1 ATP6V1A ATP6V1B1 ATP6V1B2 ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1E2 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H CASP3 CCL5 CDC42 CHUK CSK CXCL1 EGFR F11R GIT1 HBEGF IGSF5 IKBKB IKBKG IL8 IL8RA IL8RB JAM2 JAM3 JUN LYN MAP2K4 MAP3K14 MAPK10 MAPK11 MAPK12 MAPK13 MAPK14 MAPK8 MAPK9 MET NFKB1 NFKB2 NFKBIA NOD1 PAK1 PLCG1 PLCG2 PTPN11 PTPRZ1 RAC1 RELA SRC TCIRG1 TJP1
G28 ACTA1 AKT1 BDK BDKRB2 CALM1 CALM2 CALM3 CAV1 CHRM1 CHRNA1 FLT1 FLT4 HSPCA KDR NOS3 PDE2A PDE3A PDE3B PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKG1 PRKG2 RYR2 SLC7A1 SYT1 TNNI1 VEGF G29 BRAF CPEB1 EGFR ERBB2 ERBB4 ETS1 ETS2 ETV6 ETV7 FMN2 GRB2 KRAS MAP2K1 MAPK1 MAPK3 NOTCH1 NOTCH2 NOTCH3 NOTCH4 PIWIL1 PIWIL2 PIWIL3 PIWIL4 RAF1 SOS1 SOS2 SPIRE1 SPIRE2
G30 ADCY1 ADCY2 ADCY3 ADCY4 ADCY5 ADCY6 ADCY7 ADCY8 ADCY9 AKAP1 AKAP10 AKAP11 AKAP12 AKAP2 /// PALM2_AKAP2 AKAP3 AKAP4 AKAP5 AKAP6 AKAP7 AKAP8 AKAP9 ARHGEF1 CALM1 CALM2 CALM3 CHMP1B GNA11 GNA12 GNA13 GNA14 GNA15 GNAI2 GNAI3 GNAL GNAO1 GNAQ GNAZ GNB1 GNB2 GNB3 GNB5 GNG10 GNG10 /// LOC552891 GNG12 GNG13 GNG3 GNG4 GNG5 GNG7 GNGT1 GNGT2 HRAS IL18BP ITPR1 KCNJ3 KRAS MGC11266 NRAS PALM2 /// PALM2_AKAP2 PALM2_AKAP2 PDE1A PDE1B PDE1C PDE4A PDE4B PDE4C PDE4D PDE7A PDE7B PDE8A PDE8B PLCB3 PPP3CA PPP3CC PRKACA PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 PRKCD PRKCE PRKCG PRKCH PRKCI PRKCQ PRKCZ PRKD1 PRKD3 RHOA RRAS SARA1 SLC9A1 USP5
G31 ADCY1 ADCY2 ADCY3 ADCY4 ADCY5 ADCY6 ADCY7 ADCY8 ADCY9 ASIP CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CREB1 CREB3 CREB3L1 CREB3L2 CREB3L3 CREB3L4 CREBBP CTNNB1 DCT DVL1 DVL2 DVL3 EDN1 EDNRB EP300 FZD1 FZD10 FZD2 FZD3 FZD4 FZD5 FZD6 FZD7 FZD8 FZD9 GNAI1 GNAI2 GNAI3 GNAO1 GNAQ GNAS GSK3B HRAS KIT KITLG KRAS LEF1 LOC652788 MAP2K1 MAP2K2 MAPK1 MAPK3 MC1R MITF NRAS PLCB1 PLCB2 PLCB3 PLCB4 POMC PRKACA PRKACB PRKACG PRKCA PRKCB1 PRKCG PRKX PRKY RAF1 TCF7 TCF7L1 TCF7L2 TYR TYRP1 WNT1 WNT10A WNT10B WNT11 WNT16 WNT2 WNT2B WNT3 WNT3A WNT4 WNT5A WNT5B WNT6 WNT7A WNT7B WNT8A WNT8B WNT9A WNT9B G32 AKT1 APC AR ASAH1 BF BRAF CAMP CCL13 CCL15 CCL16 DAG1 EGFR GAS GNA11 GNA15 GNAI1 GNAQ ITPKA ITPKB ITPR1 ITPR2 ITPR3 KCNJ3 KCNJ5 KCNJ9 MAPK1 MAPK10 MAPK14 PHKA2 PIK3CA PIK3CD PIK3R1 PITX2 PTX1 PTX3 RAF1 SRC
G33 AKT1 CREB1 GRB2 HRAS MAPK1 MAPK3 MAPK7 MEF2A MEF2B MEF2C MEF2D NTRK1 PIK3CA PIK3R1 PLCG1 RPS6KA1 SHC1
G34 ATF2 BCR BLNK ELK1 FOS GRB2 HRAS JUN LYN MAP2K1 MAP3K1 MAPK1 MAPK3 MAPK8IP3 PAPPA RAC1 RPS6KA1 RPS6KA3 SHC1 SOS1 SYK VAV1 VAV2 VAV3
G35 CARKL FN3K IMPA1 IMPA2 INPP1 INPP4A INPP4B INPP5A INPP5B INPP5E INPPL1 IPMK ISYNA1 ITGB1BP3 ITPK1 ITPKA ITPKB MINPP1 MIOX OCRL PI4KA PI4KB PIB5PA PIK3C3 PIK3CA PIK3CB PIK3CD PIK3CG PIP4K2A PIP4K2B PIP4K2C PIP5K1A PIP5K1B PIP5K1C PIP5K3 PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCD3 PLCD4 PLCE1 PLCG1 PLCG2 PLCZ1 PTEN PTPMT1 SKIP SYNJ1 SYNJ2
G36 ADRB1 AKT1 APC ASAH1 BF CAMP CAV3 DAG1 DLG4 EPHB2 GAS GNAI1 GNAQ HTATIP ITPR1 ITPR2 ITPR3 KCNJ3 KCNJ5 KCNJ9 MAPK1 PITX2 PLB PTX1 PTX3 RAC1 RHO RYR1
G37 AGT AGTR2 BDK CALM1 CALM2 CALM3 CAMK2A CAMK2B CAMK2D CAMK2G CDK5 F2 FYN GNA11 GNAI1 GNB1 GNGT1 GRB2 HRAS JAK2 MAP2K1 MAP2K2 MAPK1 MAPK14 MAPK3 MAPK8 MAPT MYLK PLCG1 PRKCA PRKCB1 PTK2B RAF1 SHC1 SOS1 STAT1 STAT3 STAT5A SYT1
G38 ABCC8 ADIPOQ CACNA1A CACNA1B CACNA1C CACNA1D CACNA1E CACNA1G FRAP1 GCK IKBKB INS INSR IRS1 IRS2 IRS4 KCNJ11 MAFA MAPK1 MAPK10 MAPK3 MAPK8 MAPK9 PDX1 PIK3CA PIK3CB PIK3CD PIK3CG PIK3R1 PIK3R2 PIK3R3 PIK3R5 PKLR PKM2 PRKCD PRKCE PRKCZ SLC2A2 SLC2A4 SOCS1 SOCS2 SOCS3 SOCS4 TNF
G39 ADCY1 ADCY2 ADCY3 ADCY4 ADCY5 ADCY6 ADCY7 ADCY8 ADCY9 ADRB1 CDC2 CSNK1D DRD1 DRD2 EDG2 EGF EGFR GJA1 GJD2 GNA11 GNAI1 GNAI2 GNAI3 GNAQ GNAS GRB2 GRM1 GRM5 GUCY1A2 GUCY1A3 GUCY1B3 GUCY2C GUCY2D GUCY2F HRAS HTR2A HTR2B HTR2C ITPR1 ITPR2 ITPR3 KRAS LOC643224 LOC654264 MAP2K1 MAP2K2 MAP2K5 MAP3K2 MAPK1 MAPK3 MAPK7 NPR1 NPR2 NRAS PDGFA PDGFB PDGFC PDGFD PDGFRA PDGFRB PLCB1 PLCB2 PLCB3 PLCB4 PRKACA PRKACB PRKACG PRKCA PRKCB1 PRKCG PRKG1 PRKG2 PRKX PRKY RAF1 SOS1 SOS2 SRC TJP1 TUBA1A TUBA1B TUBA1C TUBA3C TUBA3D TUBA3E TUBA4A TUBA8 TUBAL3 TUBB TUBB1 TUBB2A TUBB2B TUBB2C TUBB3 TUBB4 TUBB4Q TUBB6 TUBB8 G40 ADCY1 CALM1 CALM2 CALM3 CREB1 ELK1 FOS GNAI1 GNAQ GNAS GNB1 GNGT1 HRAS JUN MAP2K1 MAPK3 NFATC1 NFATC2 NFATC3 NFATC4 PLCG1 PPP3CA PPP3CB PPP3CC PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 RAF1 RPS6KA3 SYT1
G41 ADCY1 ARHA ARHGEF1 F2 F2R F2RL3 GNA12 GNA13 GNAI1 GNAQ GNB1 GNGT1 MAP3K7 PIK3CA PIK3R1 PLCB1 PPP1R12B PRKCA PRKCB1 PTK2B ROCK1
G42 CALM1 CALM2 CALM3 CALML3 CALML6 CARKL CDIPT CDS1 CDS2 DGKA DGKB DGKD DGKE DGKG DGKH DGKI DGKQ DGKZ FN3K IMPA1 IMPA2 INPP1 INPP4A INPP4B INPP5A INPP5B INPP5D INPP5E INPPL1 ITGB1BP3 ITPK1 ITPKA ITPKB ITPR1 ITPR2 ITPR3 OCRL PI4KA PI4KB PIB5PA PIK3C2A PIK3C2B PIK3C2G PIK3C3 PIK3CA PIK3CB PIK3CD PIK3CG PIK3R1 PIK3R2 PIK3R3 PIK3R5 PIP4K2A PIP4K2B PIP4K2C PIP5K1A PIP5K1B PIP5K1C PIP5K3 PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCD3 PLCD4 PLCE1 PLCG1 PLCG2 PLCZ1 PRKCA PRKCB1 PRKCG PTEN PTPMT1 SKIP SYNJ1 SYNJ2
G43 AKT1 AVP CABIN1 CALM1 CALM2 CALM3 CAMK1 CAMK1G HDAC5 IGF1 IGF1R INS INSR MAP2K6 MAPK14 MAPK7 MEF2A MEF2B MEF2C MEF2D MYOD1 NFATC1 NFATC2 PIK3CA PIK3R1 PPP3CA PPP3CB PPP3CC SYT1 YWHAH
G44 EXT1 EXT2 EXTL1 EXTL2 EXTL3 GLCE HS2ST1 HS3ST1 HS3ST2 HS3ST3A1 HS3ST3B1 HS3ST5 HS6ST1 HS6ST2 HS6ST3 LOC728969 NDST1 NDST2 NDST3 NDST4
G45 AKT1 EIF4A1 EIF4A2 EIF4E EIF4EBP1 EIF4G1 EIF4G2 EIF4G3 FRAP1 GHR IRS1 MAPK1 MAPK14 MAPK3 MKNK1 PABPC1 PDK2 PDPK1 PIK3CA PIK3R1 PRKCA PRKCB1 PTEN RPS6KB1
G46 ADCY1 AKT1 CAMK2A CAMK2B CAMK2D CAMK2G CREB1 GNAS GRB2 HRAS MAPK1 MAPK14 MAPK3 PIK3CA PIK3R1 PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 RAC1 RPS6KA1 RPS6KA5 SOS1
G47 ACTG1 ACTG2 ADCY3 ADCY9 AK1 ARF1 ARF3 ARF4 ARF5 ARF6 ARL4D ATP6V0A1 ATP6V0A2 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0D1 ATP6V0D2 ATP6V0E1 ATP6V1A ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1E2 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H ERO1L GNAS PDIA4 PLCG1 PLCG2 PRKCA SEC61A1 SEC61A2 SEC61B SEC61G TRIM23
G48 IMPA1 INPP1 INPP4A INPP4B INPP5A INPPL1 ITPKA ITPKB MIOX OCRL PIK3C2A PIK3C2B PIK3C2G PIK3CA PIK3CB PIK3CG PIK4CA PIK4CA_///_LOC220686 PIP5K2B PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCG1 PLCG2
G49 ADCY1 ADCY2 ADCY3 ADCY4 ADCY5 ADCY6 ADCY7 ADCY8 ADCY9 ATF4 CACNA1C CACNA1D CACNA1F CACNA1S CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CDC42 CGA EGFR ELK1 FSHB GNA11 GNAQ GNAS GNRH1 GNRH2 GNRHR GRB2 HBEGF HRAS ITPR1 ITPR2 ITPR3 JUN KRAS LHB MAP2K1 MAP2K2 MAP2K3 MAP2K4 MAP2K6 MAP2K7 MAP3K1 MAP3K2 MAP3K3 MAP3K4 MAPK1 MAPK10 MAPK11 MAPK12 MAPK13 MAPK14 MAPK3 MAPK7 MAPK8 MAPK9 MMP14 MMP2 NRAS PLA2G10 PLA2G12A PLA2G12B PLA2G1B PLA2G2A PLA2G2D PLA2G2E PLA2G2F PLA2G3 PLA2G4A PLA2G5 PLA2G6 PLCB1 PLCB2 PLCB3 PLCB4 PLD1 PLD2 PRKACA PRKACB PRKACG PRKCA PRKCB1 PRKCD PRKX PRKY PTK2B RAF1 SOS1 SOS2 SRC G50 ACTA1 AGT AKT1 CALM1 CALM2 CALM3 CALR CAMK1 CAMK1G CAMK4 CREBBP CSNK1A1 CTF1 DTR EDN1 ELSPBP1 F2 FGF2 FKBP1A GATA4 GSK3B HAND1 HAND2 HRAS IGF1 LIF MAP2K1 MAPK1 MAPK14 MAPK3 MAPK8 MEF2C MYH2 NFATC1 NFATC2 NFATC3 NFATC4 NKX2-5 NPPA PIK3CA PIK3R1 PPP3CA PPP3CB PPP3CC PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B RAF1 RPS6KB1 SYT1
G51 AKT1 BAD GRB2 HRAS IGF1R IRS1 MAP2K1 MAPK1 MAPK3 PIK3CA PIK3R1 RAF1 SHC1 SOS1 YWHAH
G52 ACVR1 ACVR1B ACVRL1 AKT1 AURKB BMPR1A BMPR2 BUB1 CDC2L5 CDIPT CDKL1 CDKL2 CDS1 CDS2 CLK1 CLK2 CLK4 COL4A3BP CSNK2A1 CSNK2A1 /// CSNK2A1P CSNK2A2 CSNK2B DGKA DGKB DGKD DGKE DGKG DGKH DGKQ DGKZ IMPA1 INPP1 INPP4A INPP4B INPP5A INPPL1 ITPKA ITPKB MAP3K10 MOS NEK1 NEK3 OCRL PAK4 PCTK1 PCTK2 PIK3C2A PIK3C2B PIK3C2G PIK3CA PIK3CB PIK3CG PIK4CA PIK4CA /// LOC220686 PIM2 PIP5K2B PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCG1 PLCG2 PLK3 PRKACA PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 PRKCD PRKCE PRKCG PRKCH PRKCQ PRKCZ PRKD1 PRKG1 RAF1 RPS6KA1 RPS6KA2 RPS6KA3 RPS6KA4 RPS6KB1 STK11 TGFBR1 VRK1 G53 ADRB2 AKT1 ANXA1 CALM1 CALM2 CALM3 CRN GNAS GNB1 GNGT1 HSPCA NFKB1 NOS3 NPPA NR3C1 PIK3CA PIK3R1 RELA SYT1
G54 AKT1 AKT2 AKT3 ASAH1 BF BRAF DAG1 DRD2 EGFR EPHB2 GRB2 ITPKA ITPKB ITPR1 ITPR2 ITPR3 KCNJ3 KCNJ5 KCNJ9 MAPK1 PI3 PIK3CB PITX2 PLCB1 PLCB2 PLCB3 PLCB4 RAF1 RAP1GA1 RGS20 SHC1 SOS1 SOS2 SRC STAT3 TERF2IP
G55 CALM1 CALM2 CALM3 CD3D CD3E CD3G CD3Z ELK1 FOS FYN GRB2 HRAS JUN LAT LCK MAP2K1 MAP2K4 MAP3K1 MAPK3 MAPK8 NFATC1 NFATC2 NFATC3 NFATC4 NFKB1 NFKBIA PIK3CA PIK3R1 PLCG1 PPP3CA PPP3CB PPP3CC PRKCA PRKCB1 PTPN7 RAC1 RAF1 RASA1 RELA SHC1 SOS1 SYT1 TRA@ TRB@ VAV1 ZAP70
G56 ABL1 ACK1 ACTN1 ACTR2 ACTR3 AKT1 AKT2 AKT3 ANGPTL2 ARHGEF6 ARHGEF7 BCAR1 BRAF CAV1 CDC42 CDKN2A CRK CSE1L DDEF1 DOCK1 EPHB2 FYN GRAF GRB2 GRB7 GRF2 GRLF1 ILK ITGA1 ITGA10 ITGA11 ITGA2 ITGA3 ITGA4 ITGA5 ITGA6 ITGA7 ITGA8 ITGA9 ITGB3BP MAP2K4 MAP2K7 MAP3K11 MAPK1 MAPK10 MAPK8 MAPK8IP1 MAPK8IP2 MAPK8IP3 MAPK9 MRAS MYLK MYLK2 P4HB PAK1 PAK2 PAK3 PAK4 PAK6 PAK7 PIK3CA PIK3CB PKLR PLCG1 PLCG2 PTEN PTK2 RAF1 RALA RHO ROCK1 ROCK2 SHC1 SOS1 SOS2 SRC TERF2IP TLN1 TLN2 VASP WAS ZYX
G57 ARAF1 ATF2 BRAF CEBPA CHUK CREB1 DAXX ELK1 FOS GRB2 HRAS IKBKB JUN MAP2K1 MAP2K2 MAP2K3 MAP2K4 MAP2K5 MAP2K6 MAP2K7 MAP3K1 MAP3K10 MAP3K11 MAP3K12 MAP3K13 MAP3K14 MAP3K2 MAP3K3 MAP3K4 MAP3K5 MAP3K6 MAP3K7 MAP3K8 MAP3K9 MAP4K1 MAP4K2 MAP4K3 MAP4K4 MAP4K5 MAPK1 MAPK10 MAPK11 MAPK12 MAPK13 MAPK14 MAPK3 MAPK4 MAPK6 MAPK7 MAPK8 MAPK9 MAPKAPK2 MAPKAPK3 MAPKAPK5 MAX MEF2A MEF2B MEF2C MEF2D MKNK1 MKNK2 MYC NFKB1 NFKBIA PAK1 PAK2 PDZGEF1 RAC1 RAF1 RELA RIPK1 RPS6KA1 RPS6KA2 RPS6KA3 RPS6KA4 RPS6KA5 RPS6KB1 RPS6KB2 SHC1 SP1 STAT1 TGFB1 TGFB2 TGFB3 TGFBR1 TRADD TRAF2 G58 ALS2 BAD BAX BCL2 BCL2L1 CAT CCS GPX1 KARS NEFH NEFL NEFM PPP3CA RAB5A RAC1 SLC1A2 SOD1 SSR4 TP53
G59 ACTA1 CRK CRKL DOCK1 ELK1 FOS GAB1 GRB2 GRF2 HGF HRAS ITGA1 ITGB1 JUN MAP2K1 MAP2K2 MAP4K1 MAPK1 MAPK3 MAPK8 MET PAK1 PIK3CA PIK3R1 PTEN PTK2 PTK2B PTPN11 PXN RAF1 RAP1A RAP1B RASA1 SOS1 SRC STAT3
G60 ABAT ALDH4A1 ALDH5A1 CAD CPS1 EPRS GAD1 GAD2 GCLC GCLM GFPT1 GLS GLS2 GLUD1 GLUL GMPS GOT1 GOT2 GPT GPT2 GSS NADSYN1 PPAT QARS
G61 AKT1 AKT2 AKT3 BAD BCL2 BCR BLNK BTK CD19 CD22 CD81 CR2 CSK DAG1 FLOT1 FLOT2 GRB2 GSK3A GSK3B INPP5D ITPR1 ITPR2 ITPR3 LYN MAP4K1 MAPK1 MAPK3 NFATC1 NFATC2 NR0B2 PDK1 PIK3CA PIK3CD PIK3R1 PLCG2 PPP1R13B PPP3CA PPP3CB PPP3CC PTPRC RAF1 SHC1 SOS1 SOS2 SYK VAV1
G62 ABL1 ABL2 AKT1 AKT2 AKT3 ARAF AREG BAD BRAF BTC CAMK2A CAMK2B CAMK2D CAMK2G CBL CBLB CBLC CDKN1A CDKN1B CRK CRKL EGF EGFR EIF4EBP1 ELK1 ERBB2 ERBB3 ERBB4 EREG FRAP1 GAB1 GRB2 GSK3B HBEGF HRAS JUN KRAS MAP2K1 MAP2K2 MAP2K4 MAP2K7 MAPK1 MAPK10 MAPK3 MAPK8 MAPK9 MYC NCK1 NCK2 NRAS NRG1 NRG2 NRG3 NRG4 PAK1 PAK2 PAK3 PAK4 PAK6 PAK7 PIK3CA PIK3CB PIK3CD PIK3CG PIK3R1 PIK3R2 PIK3R3 PIK3R5 PLCG1 PLCG2 PRKCA PRKCB1 PRKCG PTK2 RAF1 RPS6KB1 RPS6KB2 SHC1 SHC2 SHC3 SHC4 SOS1 SOS2 SRC STAT5A STAT5B TGFA
G63 ACP1 ACTB ACTG1 ACTN1 ACTN2 ACTN3 ACTN4 ACVR1B ACVR1C BAIAP2 CDC42 CDH1 CREBBP CSNK2A1 CSNK2A2 CSNK2B CTNNA1 CTNNA2 CTNNA3 CTNNB1 CTNND1 EGFR EP300 ERBB2 FARP2 FER FGFR1 FYN IGF1R INSR IQGAP1 LEF1 LMO7 MAP3K7 MAPK1 MAPK3 MET MLLT4 NLK PARD3 PTPN1 PTPN6 PTPRB PTPRF PTPRJ PTPRM PVRL1 PVRL2 PVRL3 PVRL4 RAC1 RAC2 RAC3 RHOA SMAD2 SMAD3 SMAD4 SNAI1 SNAI2 SORBS1 SRC SSX2IP TCF7 TCF7L1 TCF7L2 TGFBR1 TGFBR2 TJP1 VCL WAS WASF1 WASF2 WASF3 WASL YES1
G64 ADPRT APC ASAH1 CAMP CASP3 CERK CREB1 CREB3 CREB5 CXCL2 DAG1 EPHB2 FOS GNAQ IL8RB ITPKA ITPKB JUN MAP2K4 MAP2K7 MAPK1 MAPK10 MAPK8 MAPK8IP1 MAPK8IP2 MAPK8IP3 MAPK9 PACAP
G65 ABP1 ALDH1A3 ALDH3A1 ALDH3B1 ALDH3B2 AOC2 AOC3 DDC EPX GOT1 GOT2 HPD LPO MAOA MAOB MPO PRDX1 PRDX2 PRDX5 PRDX6 TAT TPO
G66 ADRA1A ADRA1B ADRA1D ADRA2A ADRA2C ADRB1 ADRB2 ADRB3 CHRM1 CHRM2 CHRM3 CHRM4 CHRM5 DRD1 DRD2 DRD3 DRD4 DRD5 HRH1 HRH2 HTR1A HTR1B HTR1D HTR1E HTR1F HTR2A HTR2B HTR2C HTR4 HTR5A HTR6 HTR7 HTR7 /// LOC93164
G67 AKT1 ATF2 CDC42 DLD DUSP10 DUSP4 DUSP8 GAB1 GADD45A GCK IL1R1 JUN MAP2K4 MAP2K5 MAP2K7 MAP3K1 MAP3K10 MAP3K11 MAP3K12 MAP3K13 MAP3K2 MAP3K3 MAP3K4 MAP3K5 MAP3K7 MAP3K7IP1 MAP3K7IP2 MAP3K9 MAPK10 MAPK7 MAPK8 MAPK9 MYEF2 NFATC3 NR2C2 PAPPA SHC1 TP53 TRAF6 ZAK
G68 AKT1 ASAH1 ATF1 BRAF CAMP CREB1 CREB3 CREB5 CREBBP CRKL DAG1 EGR1 EGR2 EGR3 EGR4 ELK1 FRS2 GAS GNAQ GRF2 JUN MAP1B MAP2K4 MAP2K7 MAPK1 MAPK10 MAPK3 MAPK8 MAPK8IP1 MAPK8IP2 MAPK8IP3 MAPK9 NTRK1 OPN1LW PACAP PIK3C2G PIK3CA PIK3CD PIK3R1 PTPN11 RPS6KA3 SH2B SHC1 SRC TERF2IP TH TUBA3
G69 ACTR2 ACTR3 AKT1 ANGPTL2 BF DAG1 DGKA ETFA GCA ITGA9 ITPKA ITPKB ITPR1 ITPR2 ITPR3 MAP2K1 MAPK1 MAPK3 NR1I3 PAK1 PDE3A PDE3B PI3 PIK3C2G PIK3CA PIK3CD PIK3R1 PLDN PSME1 RIPK3 RPS4X SGCB VASP
G70 AKT1 AKT2 AKT3 BPNT1 GRB2 ILK MAPK1 MAPK3 PDK1 PIK3CA PIK3CD PIP3-E PTEN PTK2B RBL2 SHC1 SOS1
G71 AKT1 AKT2 AKT3 BTK CSF2 FCER1A FCER1G FYN GAB2 GRB2 HRAS IL13 IL3 IL4 IL5 INPP5D KRAS LAT LCP2 LYN MAP2K1 MAP2K2 MAP2K3 MAP2K4 MAP2K6 MAP2K7 MAPK1 MAPK10 MAPK11 MAPK12 MAPK13 MAPK14 MAPK3 MAPK8 MAPK9 MS4A2 NRAS PDK1 PIK3CA PIK3CB PIK3CD PIK3CG PIK3R1 PIK3R2 PIK3R3 PIK3R5 PLA2G10 PLA2G12A PLA2G12B PLA2G1B PLA2G2A PLA2G2D PLA2G2E PLA2G2F PLA2G3 PLA2G4A PLA2G5 PLA2G6 PLCG1 PLCG2 PRKCA PRKCB1 PRKCD PRKCE RAC1 RAC2 RAC3 RAF1 SOS1 SOS2 SYK TNF VAV1 VAV2 VAV3 Table S4 ClickTable.htm here to download Table: Table S4.pdf 2/24/11 12:49 PM
Table S4. Canonical pathways associated with tumor samples in GSEA (glioblastoma) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 ATMPATHWAY 19 0.061398175 0.32678998 0.9753 G2 CASPASEPATHWAY 22 0.041908965 0.33176932 0.9736 G3 HSA00510_N_GLYCAN_BIOSYNTHESIS 32 0.057097852 0.34436178 0.9732 G4 TELPATHWAY 15 0.071472205 0.34984782 0.9875 G5 APOPTOSIS_KEGG 48 0.057754442 0.35196567 0.9841 G6 OVARIAN_INFERTILITY_GENES 23 0.060784712 0.35210976 0.9818 G7 APOPTOSIS_GENMAPP 42 0.05961311 0.3558713 0.9941 G8 INTRINSICPATHWAY 22 0.03361846 0.35757622 0.9724 G9 HSA03030_DNA_POLYMERASE 21 0.10554245 0.35770196 0.9923 G10 MITOCHONDRIAPATHWAY 20 0.063243456 0.35891023 0.9905 G11 HSA04610_COMPLEMENT_AND_COAGULATION_CASCADES 64 0.06896552 0.3601102 0.9934 G12 HSA00500_STARCH_AND_SUCROSE_METABOLISM 59 0.053198095 0.36073875 0.9872 G13 CHEMICALPATHWAY 21 0.068993025 0.36223203 0.9962 G14 STRESSPATHWAY 24 0.10985858 0.36424825 0.9991 G15 G2PATHWAY 23 0.10566763 0.36588848 0.9991 G16 HSA00531_GLYCOSAMINOGLYCAN_DEGRADATION 16 0.087034814 0.36821327 0.9921 G17 FASPATHWAY 27 0.076612085 0.36905283 0.9956 G18 G1_TO_S_CELL_CYCLE_REACTOME 61 0.14969136 0.36958686 0.9991 G19 UBIQUITIN_MEDIATED_PROTEOLYSIS 21 0.16588546 0.369649 0.999 G20 HSA04210_APOPTOSIS 78 0.05819265 0.36966252 0.9961 G21 DNA_REPLICATION_REACTOME 43 0.13247362 0.3698926 0.9959 G22 APOPTOSIS 66 0.02921753 0.3730409 0.9719 G23 HYPERTROPHY_MODEL 19 0.11481123 0.37577033 0.9993 G24 NTHIPATHWAY 21 0.110581696 0.37744808 0.999 G25 G1PATHWAY 25 0.0829754 0.37760243 0.9979 G26 CELL_CYCLE_KEGG 79 0.06863512 0.37832397 0.968 G27 HSA03022_BASAL_TRANSCRIPTION_FACTORS 28 0.11677798 0.3790801 0.9977 G28 MITOCHONDRIAL_FATTY_ACID_BETAOXIDATION 15 0.04442289 0.380543 0.964 G29 PROTEASOMEPATHWAY 21 0.2026538 0.3805722 0.9996 G30 STARCH_AND_SUCROSE_METABOLISM 29 0.090998426 0.381138 0.9974 G31 TNFR1PATHWAY 28 0.08836735 0.3845496 0.999 G32 N_GLYCAN_BIOSYNTHESIS 21 0.14062198 0.38554227 0.9996 G33 PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 18 0.115605794 0.3860754 0.9987 G34 PROTEASOME 16 0.15759027 0.3883238 0.9996 G35 HSA05210_COLORECTAL_CANCER 81 0.059790425 0.3899884 0.9985 G36 HSA04330_NOTCH_SIGNALING_PATHWAY 37 0.13948841 0.39129 0.999 G37 HSA00860_PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 27 0.14421365 0.39411703 0.9998 G38 ARFPATHWAY 15 0.120872974 0.3944469 0.9998 G39 TNFR2PATHWAY 18 0.05791191 0.40132686 0.9635 G40 NFKBPATHWAY 23 0.04550071 0.41563112 0.962 G41 DEATHPATHWAY 32 0.033411488 0.42707497 0.9487 G42 HSA05212_PANCREATIC_CANCER 71 0.08716513 0.43343326 1 G43 HSA00240_PYRIMIDINE_METABOLISM 70 0.05258916 0.43821436 0.9609 G44 TRANSLATION_FACTORS 43 0.19454473 0.44073012 1 G45 HSA01032_GLYCAN_STRUCTURES_DEGRADATION 26 0.057302028 0.4410917 0.9445 G46 RNA_TRANSCRIPTION_REACTOME 33 0.22633663 0.4477027 1 G47 TIDPATHWAY 17 0.037089013 0.45166355 0.9371 G48 STATIN_PATHWAY_PHARMGKB 16 0.16375811 0.45255196 1 G49 HSA04512_ECM_RECEPTOR_INTERACTION 80 0.18896551 0.45461285 1 G50 HSA05220_CHRONIC_MYELOID_LEUKEMIA 74 0.1376438 0.45647827 1 G51 HSA00310_LYSINE_DEGRADATION 40 0.14378585 0.45933974 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 12:49 PM
G52 IL1RPATHWAY 30 0.16896753 0.46079493 1 G53 TOLLPATHWAY 30 0.22673267 0.47048888 1 G54 CERAMIDEPATHWAY 22 0.19906844 0.4709327 1 G55 41BBPATHWAY 18 0.19499287 0.47193536 1 G56 P53HYPOXIAPATHWAY 18 0.2031493 0.47211686 1 G57 LAIRPATHWAY 15 0.2070528 0.47371286 1 G58 HSA05217_BASAL_CELL_CARCINOMA 45 0.18270008 0.4762505 1 G59 CTLA4PATHWAY 17 0.23140022 0.476948 1 G60 HSA05215_PROSTATE_CANCER 84 0.14297302 0.47805128 1 G61 HSA05219_BLADDER_CANCER 41 0.128287 0.48135838 1 G62 HSA05040_HUNTINGTONS_DISEASE 27 0.18726236 0.48501563 1 G63 HSA05216_THYROID_CANCER 29 0.17655012 0.487 1 G64 ATRBRCAPATHWAY 20 0.042060778 0.4907708 0.9363 G65 LYSINE_DEGRADATION 28 0.19636433 0.49789548 1 G66 HSA04350_TGF_BETA_SIGNALING_PATHWAY 81 0.19006816 0.4979371 1 G67 PROSTAGLANDIN_AND_LEUKOTRIENE_METABOLISM 30 0.26255128 0.50365865 1 G68 HSA05010_ALZHEIMERS_DISEASE 24 0.21424435 0.50407225 1 G69 IL2RBPATHWAY 34 0.23678522 0.50647587 1 G70 PROSTAGLANDIN_SYNTHESIS_REGULATION 27 0.2172487 0.50811183 1 G71 HSP27PATHWAY 15 0.035820305 0.5094309 0.9286 G72 ST_TUMOR_NECROSIS_FACTOR_PATHWAY 29 0.27439886 0.5095479 1 G73 GLYCOSPHINGOLIPID_METABOLISM 21 0.2750049 0.5272521 1 G74 HSA04612_ANTIGEN_PROCESSING_AND_PRESENTATION 73 0.06461233 0.5299022 0.92 G75 CARDIACEGFPATHWAY 17 0.26396647 0.53057295 1 G76 BLOOD_CLOTTING_CASCADE 19 0.27215955 0.53143585 1 G77 BREAST_CANCER_ESTROGEN_SIGNALING 91 0.21943273 0.53214556 1 G78 HSA00770_PANTOTHENATE_AND_COA_BIOSYNTHESIS 15 0.30859932 0.5332503 1 G79 HSA05050_DENTATORUBROPALLIDOLUYSIAN_ATROPHY 15 0.23194964 0.5338842 1 G80 HIVNEFPATHWAY 54 0.02314151 0.5339835 0.9013 G81 RACCYCDPATHWAY 22 0.27075452 0.5341166 1 G82 CELLCYCLEPATHWAY 22 0.2966443 0.5346158 1 G83 HSA04115_P53_SIGNALING_PATHWAY 62 0.012660772 0.59642214 0.8971 G84 ST_FAS_SIGNALING_PATHWAY 59 0.25524476 0.60875875 1 G85 GSK3PATHWAY 25 0.297516 0.6092716 1 G86 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY 97 0.35770184 0.6133311 1 G87 NKTPATHWAY 25 0.3768814 0.6151288 1 G88 SA_CASPASE_CASCADE 16 0.37004066 0.62895113 1 G89 HSA05221_ACUTE_MYELOID_LEUKEMIA 52 0.3041511 0.6347967 1 G90 VEGFPATHWAY 27 0.35660797 0.6389697 1 G91 TOB1PATHWAY 16 0.400999 0.6417481 1 G92 HSA00790_FOLATE_BIOSYNTHESIS 35 0.36526588 0.64412916 1 G93 INFLAMPATHWAY 29 0.40791076 0.648757 1 G94 HSA00563_GLYCOSYLPHOSPHATIDYLINOSITOL_ANCHOR_BIOSYNTHESIS 18 0.38565737 0.65515745 1 G95 RIBOSOMAL_PROTEINS 81 0.08998549 0.66124135 0.8868 G96 TH1TH2PATHWAY 17 0.46671948 0.6714784 1 G97 AMINOACYL_TRNA_BIOSYNTHESIS 20 0.39698285 0.6722138 1 G98 ARAPPATHWAY 20 0.40419582 0.6743601 1 G99 HSA05213_ENDOMETRIAL_CANCER 50 0.42652768 0.693224 1 G100 HSA01030_GLYCAN_STRUCTURES_BIOSYNTHESIS_1 81 0.42227685 0.6947543 1 G101 ST_ERK1_ERK2_MAPK_PATHWAY 29 0.43629497 0.70277876 1 G102 PITX2PATHWAY 16 0.45134532 0.7082076 1 G103 HSA03050_PROTEASOME 22 0.46385053 0.710667 1 G104 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS 32 0.44833004 0.7114526 1 G105 EICOSANOID_SYNTHESIS 16 0.5111705 0.7388618 1 G106 HSA04940_TYPE_I_DIABETES_MELLITUS 39 0.48315048 0.7389732 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 12:49 PM
G107 HSA00970_AMINOACYL_TRNA_BIOSYNTHESIS 26 0.46377105 0.7430523 1 G108 P53PATHWAY 16 0.015690168 0.7444809 0.8742 G109 HSA00760_NICOTINATE_AND_NICOTINAMIDE_METABOLISM 16 0.5488241 0.7602142 1 G110 GALACTOSE_METABOLISM 22 0.5385217 0.7644694 1 G111 HSA04614_RENIN_ANGIOTENSIN_SYSTEM 15 0.5467135 0.76944363 1 G112 HSA05131_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EPEC 41 0.5201374 0.76948136 1 G113 HSA00480_GLUTATHIONE_METABOLISM 32 0.5134209 0.77140224 1 G114 HSA04640_HEMATOPOIETIC_CELL_LINEAGE 80 0.54203624 0.77529484 1 G115 HSA05130_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EHEC 41 0.5201374 0.7761148 1 G116 ECMPATHWAY 21 0.5031319 0.7785526 1 G117 RASPATHWAY 22 0.54429877 0.7980754 1 G118 ALKPATHWAY 32 0.59186095 0.80022526 1 G119 HSA00591_LINOLEIC_ACID_METABOLISM 27 0.64529574 0.82105994 1 G120 INTEGRIN_MEDIATED_CELL_ADHESION_KEGG 83 0.59937465 0.82207805 1 G121 INTEGRINPATHWAY 32 0.6058108 0.8253467 1 G122 HSA00590_ARACHIDONIC_ACID_METABOLISM 48 0.65495825 0.8280631 1 G123 SPPAPATHWAY 20 0.64141023 0.83095735 1 G124 HSA00565_ETHER_LIPID_METABOLISM 27 0.6335637 0.8312089 1 G125 ST_P38_MAPK_PATHWAY 35 0.63981044 0.8320407 1 G126 HSA04670_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION 100 0.66502756 0.8321245 1 G127 HSA00071_FATTY_ACID_METABOLISM 39 0.625902 0.83305234 1 G128 HSA00512_O_GLYCAN_BIOSYNTHESIS 20 0.6696638 0.833968 1 G129 MCALPAINPATHWAY 22 0.6679624 0.83540714 1 G130 HSA03020_RNA_POLYMERASE 18 0.5757456 0.8357855 1 G131 HSA00530_AMINOSUGARS_METABOLISM 26 0.60883766 0.8360648 1 G132 SPRYPATHWAY 16 0.59782606 0.8373639 1 G133 HSA04662_B_CELL_RECEPTOR_SIGNALING_PATHWAY 59 0.69855523 0.8382003 1 G134 FRUCTOSE_AND_MANNOSE_METABOLISM 24 0.67384917 0.839724 1 G135 SMALL_LIGAND_GPCRS 17 0.6672244 0.8401523 1 G136 CYTOKINEPATHWAY 20 0.6829653 0.8402391 1 G137 HSA00051_FRUCTOSE_AND_MANNOSE_METABOLISM 36 0.6861286 0.84525305 1 G138 HSA05223_NON_SMALL_CELL_LUNG_CANCER 52 0.74155766 0.8462067 1 G139 IGF1MTORPATHWAY 20 0.66765875 0.84917796 1 G140 IL3PATHWAY 15 0.70508003 0.85675997 1 G141 ST_INTERLEUKIN_4_PATHWAY 26 0.7256897 0.8621677 1 G142 HSA03010_RIBOSOME 55 0.055001017 0.87125236 0.8601 G143 HCMVPATHWAY 15 0.73219204 0.8714468 1 G144 HSA00624_1_AND_2_METHYLNAPHTHALENE_DEGRADATION 16 0.7571942 0.872491 1 G145 IL7PATHWAY 16 0.7411604 0.8737992 1 G146 UCALPAINPATHWAY 15 0.7075929 0.8772437 1 G147 HSA02010_ABC_TRANSPORTERS_GENERAL 35 0.8243677 0.88311106 1 G148 HSA00450_SELENOAMINO_ACID_METABOLISM 24 0.7662179 0.8943341 1 G149 IL6PATHWAY 21 0.7532292 0.89575505 1 G150 HSA00030_PENTOSE_PHOSPHATE_PATHWAY 25 0.828125 0.8966395 1 G151 HSA00120_BILE_ACID_BIOSYNTHESIS 31 0.8462739 0.8993556 1 G152 HSA00052_GALACTOSE_METABOLISM 27 0.7979175 0.9001659 1 G153 HSA00361_GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 19 0.78394103 0.9004569 1 G154 GLUTATHIONE_METABOLISM 27 0.826213 0.902372 1 G155 DCPATHWAY 20 0.7818529 0.9107552 1 G156 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES 34 0.9157793 0.9242359 1 G157 CSKPATHWAY 20 0.8243452 0.9269742 1 G158 MTORPATHWAY 23 0.77545637 0.92915386 1 G159 AMIPATHWAY 20 0.8243452 0.93276775 1 G160 HSA00271_METHIONINE_METABOLISM 16 0.9010288 0.95964956 1 G161 AKTPATHWAY 17 0.91126347 0.9634356 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 12:49 PM
G162 RARRXRPATHWAY 15 0.87709385 0.9684959 1 G163 RELAPATHWAY 16 0.015505479 0.97404665 0.7067 G164 CARM_ERPATHWAY 26 0.90914273 0.97608966 1 G165 GLYCINE_SERINE_AND_THREONINE_METABOLISM 30 0.966133 0.97642225 1 G166 HSA04950_MATURITY_ONSET_DIABETES_OF_THE_YOUNG 18 0.9841817 0.9843397 1 G167 HSA00220_UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS 27 0.98624563 0.98440343 1 G168 HSA00632_BENZOATE_DEGRADATION_VIA_COA_LIGATION 23 0.98299384 0.9875915 1 G169 HSA00260_GLYCINE_SERINE_AND_THREONINE_METABOLISM 36 0.98539555 0.98845965 1 G170 STEMPATHWAY 15 0.9834502 0.99198407 1 G171 HSA00903_LIMONENE_AND_PINENE_DEGRADATION 24 0.9888995 0.9921071 1 G172 HSA05222_SMALL_CELL_LUNG_CANCER 87 0.014636157 1 0.8494 G173 PYRIMIDINE_METABOLISM 55 0.014909919 1 0.6543
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S5a ClickTable.htm here to download Table: Table S5a.pdf 2/24/11 3:40 PM
Table S5a. Canonical pathways associated with normal samples in GSEA (glioblastoma) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 HDACPATHWAY 29 0.025540275 0.17286189 0.8201 G2 NOS1PATHWAY 21 0.001318392 0.18178187 0.8193 G3 PYRUVATE_METABOLISM 34 0.042762455 0.1836509 0.8778 G4 GPCRPATHWAY 33 0.020131383 0.18396196 0.8587 G5 G_PROTEIN_SIGNALING 85 0.008822233 0.18400821 0.8477 G6 CK1PATHWAY 15 0.007392912 0.18536298 0.8705 G7 HSA04070_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 67 0.020368364 0.18560062 0.887 G8 BIOPEPTIDESPATHWAY 38 0.009564294 0.1903107 0.7847 G9 HSA04930_TYPE_II_DIABETES_MELLITUS 40 0.022044929 0.19044363 0.9012 G10 HSA00562_INOSITOL_PHOSPHATE_METABOLISM 40 0.012948419 0.19062437 0.817 G11 PGC1APATHWAY 23 0.000659486 0.1932041 0.8052 G12 FMLPPATHWAY 34 0.028645834 0.19522098 0.9236 G13 HSA04740_OLFACTORY_TRANSDUCTION 28 0.027641932 0.19652992 0.913 G14 HSA04720_LONG_TERM_POTENTIATION 66 0.001338987 0.19818692 0.6445 G15 HSA04912_GNRH_SIGNALING_PATHWAY 92 0.011283798 0.19860017 0.9312 G16 BUTANOATE_METABOLISM 26 0.028181227 0.20041078 0.9225 G17 CCR3PATHWAY 22 0.023285352 0.20186274 0.7818 G18 PHOTOSYNTHESIS 19 0.028565599 0.20355438 0.7412 G19 PYK2PATHWAY 27 0.014724443 0.20731133 0.7216 G20 MONOAMINE_GPCRS 28 0.011274935 0.2097747 0.6968 G21 NFATPATHWAY 50 0.007237122 0.21156266 0.6287 G22 AT1RPATHWAY 34 0.014542344 0.21728715 0.7817 G23 PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 85 0.002345916 0.22146004 0.6008 G24 NDKDYNAMINPATHWAY 17 0.02336945 0.22265233 0.9675 G25 HSA04730_LONG_TERM_DEPRESSION 73 0.019616487 0.22587174 0.9665 G26 CREBPATHWAY 26 0.037608694 0.23181279 0.9662 G27 HSA00650_BUTANOATE_METABOLISM 40 0.047679324 0.23206964 0.9531 G28 CARBON_FIXATION 19 0.06532357 0.23265219 0.9631 G29 INOSITOL_PHOSPHATE_METABOLISM 22 0.04721823 0.23837456 0.9626 G30 TYPE_III_SECRETION_SYSTEM 18 0.010550269 0.23934576 0.5174 G31 ST_WNT_CA2_CYCLIC_GMP_PATHWAY 19 0.032934133 0.24289514 0.9613 G32 SIG_CD40PATHWAYMAP 33 0.01174743 0.25212583 0.5935 G33 HSA04540_GAP_JUNCTION 85 0.018660812 0.26243457 0.982 G34 FLAGELLAR_ASSEMBLY 18 0.010550269 0.29918218 0.5174 G35 MEF2DPATHWAY 17 0.079467446 0.30596548 0.9915 G36 GLUTAMATE_METABOLISM 22 0.05172414 0.3097077 0.9911 G37 HSA00251_GLUTAMATE_METABOLISM 27 0.04563873 0.3098349 0.9898 G38 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS 43 0.071400076 0.31557807 0.9932 G39 HSA05110_CHOLERA_INFECTION 36 0.080349706 0.33032095 0.9946 G40 HSA00252_ALANINE_AND_ASPARTATE_METABOLISM 28 0.08630635 0.33473772 0.9953 G41 HSA00620_PYRUVATE_METABOLISM 36 0.104606114 0.3415729 0.9959 G42 HSA04012_ERBB_SIGNALING_PATHWAY 84 0.045387685 0.34652475 0.9966 G43 VIPPATHWAY 25 0.08426847 0.3470141 0.9966 G44 PHENYLALANINE_METABOLISM 20 0.11213048 0.35078487 0.998
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 3:40 PM
G45 ST_T_CELL_SIGNAL_TRANSDUCTION 42 0.063068785 0.3534192 0.9965 G46 CALCINEURINPATHWAY 18 0.099958435 0.3537677 0.9976 G47 HSA04916_MELANOGENESIS 90 0.044327732 0.35544187 0.9974 G48 RAC1PATHWAY 22 0.088821135 0.36045447 0.9987 G49 HSA00710_CARBON_FIXATION 21 0.13722566 0.3615318 0.999 G50 HSA01031_GLYCAN_STRUCTURES_BIOSYNTHESIS_2 53 0.0725945 0.36168784 0.9982 G51 TCRPATHWAY 42 0.10032962 0.36405274 0.9985 G52 PTDINSPATHWAY 20 0.10791513 0.36434445 0.999 G53 ST_GRANULE_CELL_SURVIVAL_PATHWAY 27 0.099042185 0.37965503 0.9994 G54 ALANINE_AND_ASPARTATE_METABOLISM 18 0.12292994 0.38003188 0.9994 G55 ST_G_ALPHA_I_PATHWAY 34 0.064550266 0.3845531 0.9994 G56 GLYCOLYSIS_AND_GLUCONEOGENESIS 42 0.1539252 0.38794115 0.9995 G57 HSA00190_OXIDATIVE_PHOSPHORYLATION 98 0.2449848 0.3934046 0.9995 G58 NO1PATHWAY 27 0.11597327 0.39399675 0.9995 G59 SIG_CHEMOTAXIS 42 0.09452631 0.39400545 0.9995 G60 ATP_SYNTHESIS 18 0.010550269 0.3989096 0.5174 G61 CHREBPPATHWAY 16 0.17990848 0.41484123 0.9998 G62 SA_PTEN_PATHWAY 17 0.14285715 0.4498111 1 G63 HSA05030_AMYOTROPHIC_LATERAL_SCLEROSIS 17 0.178249 0.45101255 1 G64 BCRPATHWAY 34 0.15982765 0.45369196 1 G65 OXIDATIVE_PHOSPHORYLATION 54 0.035318274 0.47122848 0.4468 G66 ST_GA12_PATHWAY 21 0.15346122 0.47132728 1 G67 EDG1PATHWAY 25 0.15495008 0.47268653 1 G68 KREBS_TCA_CYCLE 26 0.23907667 0.47906816 1 G69 HSA00602_GLYCOSPHINGOLIPID_BIOSYNTHESIS_NEO_LACTOS20 0.16829316 0.4794058 1 G70 CHOLESTEROL_BIOSYNTHESIS 15 0.29973954 0.5005187 1 G71 BADPATHWAY 21 0.18330571 0.50724745 1 G72 HSA05211_RENAL_CELL_CARCINOMA 67 0.13997945 0.5122363 1 G73 SIG_PIP3_SIGNALING_IN_CARDIAC_MYOCTES 64 0.1600169 0.5137856 1 G74 HSA00350_TYROSINE_METABOLISM 48 0.18306068 0.52900064 1 G75 BILE_ACID_BIOSYNTHESIS 23 0.2314602 0.5308975 1 G76 HSA00150_ANDROGEN_AND_ESTROGEN_METABOLISM 40 0.22202452 0.53147364 1 G77 SIG_REGULATION_OF_THE_ACTIN_CYTOSKELETON_BY_RHO_G33 0.22511648 0.5457814 1 G78 ANDROGEN_AND_ESTROGEN_METABOLISM 22 0.24945983 0.55247504 1 G79 PAR1PATHWAY 19 0.2519291 0.5539725 1 G80 ST_GAQ_PATHWAY 27 0.22062398 0.55593973 1 G81 NUCLEAR_RECEPTORS 38 0.238343 0.56786585 1 G82 HSA00564_GLYCEROPHOSPHOLIPID_METABOLISM 55 0.20089924 0.5686863 1 G83 HSA00980_METABOLISM_OF_XENOBIOTICS_BY_CYTOCHROM50 0.2855359 0.5699415 1 G84 HSA04140_REGULATION_OF_AUTOPHAGY 28 0.2728335 0.5720291 1 G85 TYROSINE_METABOLISM 27 0.25097156 0.57260597 1 G86 ST_MYOCYTE_AD_PATHWAY 24 0.24018806 0.57283425 1 G87 FCER1PATHWAY 37 0.22984952 0.5776116 1 G88 MAPKPATHWAY 84 0.25638407 0.5800101 1 G89 PEPTIDE_GPCRS 68 0.28252032 0.58252066 1 G90 HSA00360_PHENYLALANINE_METABOLISM 26 0.2844372 0.58446115 1 G91 GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 26 0.30845565 0.5866021 1 G92 CCR5PATHWAY 17 0.3085971 0.58718383 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 3:40 PM
G93 GLYCOLYSIS 48 0.28296146 0.58885115 1 G94 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_CHEMOTAXIS_PATH30 0.3131271 0.5902959 1 G95 CDMACPATHWAY 16 0.33771753 0.591473 1 G96 GPCRDB_OTHER 47 0.29286164 0.59409696 1 G97 ST_JNK_MAPK_PATHWAY 40 0.29029655 0.5945675 1 G98 GLUCONEOGENESIS 48 0.28296146 0.59546745 1 G99 IGF1RPATHWAY 15 0.36203176 0.595889 1 G100 ERK5PATHWAY 17 0.30908728 0.5972361 1 G101 HSA00534_HEPARAN_SULFATE_BIOSYNTHESIS 16 0.2972287 0.5976053 1 G102 GLYCEROLIPID_METABOLISM 39 0.299303 0.59846675 1 G103 PDGFPATHWAY 27 0.34556815 0.5988394 1 G104 IGF1PATHWAY 20 0.35963902 0.60089386 1 G105 HSA00330_ARGININE_AND_PROLINE_METABOLISM 29 0.29143447 0.60184073 1 G106 CXCR4PATHWAY 23 0.3591012 0.6031589 1 G107 HSA01510_NEURODEGENERATIVE_DISEASES 35 0.3305192 0.603629 1 G108 HSA05120_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_P61 0.34348357 0.6104984 1 G109 ST_INTEGRIN_SIGNALING_PATHWAY 75 0.33401597 0.6170985 1 G110 RHOPATHWAY 29 0.4157189 0.62099814 1 G111 HSA00410_BETA_ALANINE_METABOLISM 24 0.39002267 0.62306625 1 G112 HSA04150_MTOR_SIGNALING_PATHWAY 44 0.38205785 0.6231635 1 G113 HSA00910_NITROGEN_METABOLISM 23 0.38334394 0.6241343 1 G114 METPATHWAY 33 0.38782746 0.6255664 1 G115 HSA00561_GLYCEROLIPID_METABOLISM 48 0.36851853 0.6293973 1 G116 BETA_ALANINE_METABOLISM 25 0.3795757 0.6294718 1 G117 HSA00100_BIOSYNTHESIS_OF_STEROIDS 23 0.4322267 0.6418902 1 G118 ST_WNT_BETA_CATENIN_PATHWAY 28 0.40611452 0.6459115 1 G119 HSA04370_VEGF_SIGNALING_PATHWAY 66 0.4201783 0.6621505 1 G120 HISTIDINE_METABOLISM 23 0.45621642 0.66499317 1 G121 HSA04920_ADIPOCYTOKINE_SIGNALING_PATHWAY 68 0.46458462 0.675983 1 G122 HSA00020_CITRATE_CYCLE 23 0.45013532 0.6764267 1 G123 ACTINYPATHWAY 16 0.46691027 0.6773544 1 G124 HSA04660_T_CELL_RECEPTOR_SIGNALING_PATHWAY 90 0.43142733 0.67855704 1 G125 ST_ADRENERGIC 33 0.45641232 0.6790624 1 G126 HSA05214_GLIOMA 62 0.484193 0.67906487 1 G127 GLYCEROPHOSPHOLIPID_METABOLISM 45 0.4708384 0.68134964 1 G128 EIF4PATHWAY 24 0.49161664 0.68945676 1 G129 NITROGEN_METABOLISM 20 0.5071942 0.69389147 1 G130 ST_GA13_PATHWAY 35 0.5092037 0.6975328 1 G131 CALCINEURIN_NF_AT_SIGNALING 90 0.54886454 0.6985483 1 G132 INSULINPATHWAY 21 0.4954677 0.69915557 1 G133 KERATINOCYTEPATHWAY 43 0.5666802 0.6998366 1 G134 ERKPATHWAY 30 0.57966524 0.70056385 1 G135 ARGININE_AND_PROLINE_METABOLISM 40 0.5154767 0.70128375 1 G136 PROPANOATE_METABOLISM 29 0.52712685 0.7028797 1 G137 ETSPATHWAY 15 0.5192878 0.7036042 1 G138 EGFPATHWAY 27 0.5392558 0.7051632 1 G139 MPRPATHWAY 22 0.52996844 0.705375 1 G140 HSA00340_HISTIDINE_METABOLISM 33 0.55173826 0.70551306 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 3:40 PM
G141 WNT_SIGNALING 58 0.5890074 0.7084368 1 G142 HSA00010_GLYCOLYSIS_AND_GLUCONEOGENESIS 55 0.5672586 0.7088972 1 G143 TPOPATHWAY 23 0.5355798 0.7100439 1 G144 HSA04320_DORSO_VENTRAL_AXIS_FORMATION 23 0.53434384 0.7128785 1 G145 NKCELLSPATHWAY 17 0.5946002 0.7261839 1 G146 HSA04340_HEDGEHOG_SIGNALING_PATHWAY 45 0.60295564 0.72785825 1 G147 CIRCADIAN_EXERCISE 39 0.598334 0.7368312 1 G148 WNTPATHWAY 25 0.6135441 0.75130796 1 G149 TRYPTOPHAN_METABOLISM 51 0.6482278 0.7697003 1 G150 HSA04664_FC_EPSILON_RI_SIGNALING_PATHWAY 73 0.67254156 0.77861035 1 G151 GPCRDB_CLASS_B_SECRETIN_LIKE 22 0.70367426 0.7817095 1 G152 SIG_IL4RECEPTOR_IN_B_LYPHOCYTES 27 0.7172537 0.79343045 1 G153 GHPATHWAY 27 0.68023854 0.79726887 1 G154 GLEEVECPATHWAY 22 0.67152727 0.79766554 1 G155 EPOPATHWAY 19 0.6754351 0.798445 1 G156 IL12PATHWAY 19 0.65295845 0.79945 1 G157 HSA04130_SNARE_INTERACTIONS_IN_VESICULAR_TRANSPORT30 0.69357216 0.80208236 1 G158 CITRATE_CYCLE_TCA_CYCLE 19 0.6118236 0.8024108 1 G159 HSA05218_MELANOMA 68 0.8615813 0.8057037 1 G160 PENTOSE_PHOSPHATE_PATHWAY 22 0.7238348 0.8063884 1 G161 P38MAPKPATHWAY 39 0.8113438 0.8145841 1 G162 SA_B_CELL_RECEPTOR_COMPLEXES 24 0.75563157 0.83891404 1 G163 HSA04520_ADHERENS_JUNCTION 72 0.83451635 0.84137535 1 G164 NGFPATHWAY 19 0.75580025 0.8568604 1 G165 HSA00380_TRYPTOPHAN_METABOLISM 49 0.8516048 0.8603368 1 G166 HSA03320_PPAR_SIGNALING_PATHWAY 59 0.8793991 0.8775563 1 G167 STRIATED_MUSCLE_CONTRACTION 33 0.8364989 0.8824616 1 G168 NO2IL12PATHWAY 15 0.7864203 0.8993356 1 G169 PTENPATHWAY 16 0.8118132 0.90109324 1 G170 GCRPATHWAY 17 0.891389 0.9042927 1 G171 PPARAPATHWAY 51 0.9243979 0.9065313 1 G172 HSA04742_TASTE_TRANSDUCTION 34 0.001475859 0.9068186 0.4367 G173 SIG_BCR_SIGNALING_PATHWAY 44 0.82833403 0.9069496 1 G174 VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 34 0.9165434 0.9125573 1 G175 IL2PATHWAY 22 0.8103158 0.9143446 1 G176 ST_B_CELL_ANTIGEN_RECEPTOR 39 0.8908938 0.9150396 1 G177 HSA00960_ALKALOID_BIOSYNTHESIS_II 15 0.8971394 0.92528504 1 G178 SIG_INSULIN_RECEPTOR_PATHWAY_IN_CARDIAC_MYOCYTES 50 0.9414585 0.93043953 1 G179 SA_TRKA_RECEPTOR 16 0.9260708 0.95066005 1 G180 UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS 16 0.9665101 0.9663099 1 G181 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY 33 0.97982883 0.96749264 1 G182 HSA00280_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATIO 42 0.98071337 0.9743332 1 G183 HSA00600_SPHINGOLIPID_METABOLISM 29 0.98159635 0.9750018 1 G184 HSA00640_PROPANOATE_METABOLISM 29 0.9640855 0.97982925 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S5b ClickTable.htm here to download Table: Table S5b.pdf 2/24/11 1:03 PM
Table S5b. Canonical pathways associated with normal samples in GSEA (glioblastoma) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 BIOCARTA_HDAC_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_HDAC_PATHWAY.html G2 BIOCARTA_NOS1_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NOS1_PATHWAY.html G3 KEGG_PYRUVATE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PYRUVATE_METABOLISM.html G4 BIOCARTA_GPCR_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_GPCR_PATHWAY.html G5 N/A N/A G6 BIOCARTA_CK1_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CK1_PATHWAY.html G7 KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM.html G8 BIOCARTA_BIOPEPTIDES_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_BIOPEPTIDES_PATHWAY.html G9 KEGG_TYPE_II_DIABETES_MELLITUS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_TYPE_II_DIABETES_MELLITUS.html G10 KEGG_INOSITOL_PHOSPHATE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_INOSITOL_PHOSPHATE_METABOLISM.html G11 BIOCARTA_PGC1A_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_PGC1A_PATHWAY.html G12 BIOCARTA_FMLP_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_FMLP_PATHWAY.html G13 KEGG_OLFACTORY_TRANSDUCTION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_OLFACTORY_TRANSDUCTION.html G14 KEGG_LONG_TERM_POTENTIATION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_LONG_TERM_POTENTIATION.html G15 KEGG_GNRH_SIGNALING_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GNRH_SIGNALING_PATHWAY.html G16 KEGG_BUTANOATE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_BUTANOATE_METABOLISM.html G17 BIOCARTA_CCR3_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CCR3_PATHWAY.html G18 N/A N/A G19 BIOCARTA_PYK2_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_PYK2_PATHWAY.html G20 N/A N/A G21 BIOCARTA_NFAT_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NFAT_PATHWAY.html G22 BIOCARTA_AT1R_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_AT1R_PATHWAY.html G23 KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM.html G24 BIOCARTA_NDKDYNAMIN_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NDKDYNAMIN_PATHWAY.html G25 KEGG_LONG_TERM_DEPRESSION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_LONG_TERM_DEPRESSION.html G26 BIOCARTA_CREB_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_CREB_PATHWAY.html G27 KEGG_BUTANOATE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_BUTANOATE_METABOLISM.html G28 N/A N/A G29 KEGG_INOSITOL_PHOSPHATE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_INOSITOL_PHOSPHATE_METABOLISM.html G30 N/A N/A G31 ST_WNT_CA2_CYCLIC_GMP_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_WNT_CA2_CYCLIC_GMP_PATHWAY.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S5c ClickTable.htm here to download Table: Table S5c.pdf 2/24/11 1:06 PM
Table S5c. Canonical pathways associated with normal samples in GSEA (glioblastoma) Sorted by FDR Index Description G1 Myocyte enhancer factor MEF2 activates transcription of genes required for muscle cell differentiation and is inhibited by histone deacetylases. G2 Glutamate stimulates NMDA-mediates calcium influx, which promotes nitric oxide synthesis from arginine by neuronal nitric oxide synthase, activating guanylate cyclase. G3 N/A G4 G-protein coupled receptors activate adenylyl cyclase, which converts ATP to cAMP, to activate second messenger pathways. G5 N/A G6 Caseine kinase 1 (CK1) and cdk5 phosphorylate DARPP32 in the dopamine signaling pathway. G7 Genes involved in phosphatidylinositol signaling system G8 Extracellular signaling peptides exert biological effects via G-protein coupled receptors (GPCRs), which activate intracellular GTPases. G9 Genes involved in type II diabetes mellitus G10 Genes involved in inositol phosphate metabolism G11 PCG-1a is expressed in skeletal muscle, heart muscle, and brown fat, and is a coactivator for receptors such as glucocorticoid receptor and thyroid hormone receptor. G12 The fMLP receptor is a G-protein coupled receptor in neutrophils that recognizes formylated bacterial peptides and activates NADPH oxidase. G13 Genes involved in olfactory transduction G14 Genes involved in long-term potentiation G15 Genes involved in GnRH signaling pathway G16 N/A G17 CCR3 is a G-protein coupled receptor that recruits eosinophils to inflammation sites via chemokine ligands. G18 N/A G19 Pyk2 and Rac1 stimulate the JNK cascade and activate MKK3, which activates p38. G20 N/A G21 Cardiac hypertrophy is induced by NF-ATc4 and GATA4, which are stimulated through calcineurin activated by CaMK. G22 Binding of angiotensin II to AT1-R activates Ca2+ signaling and the JNK pathway. G23 N/A G24 Endocytotic role of NDK, Phosphins and Dynamin G25 Genes involved in long-term depression G26 CREB is a transcription factor that binds to cAMP-responsive elements (CREs) to activate transcription in response to extracellular signaling. G27 Genes involved in butanoate metabolism G28 N/A G29 G30 N/A G31 Some Wnt glycoprotein/Frizzled receptor interactions increase intracellular calcium and decrease cGMP.
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S5d Click here to download Table: Table S5d.pdf
Table S5d. Canonical pathways associated with normal samples in GSEA (glioblastoma)
Sorted by FDR
Index Genes
G1 AKT1 AVP CABIN1 CALM1 CALM2 CALM3 CAMK1 CAMK1G HDAC5 IGF1 IGF1R INS INSR MAP2K6 MAPK14 MAPK7 MEF2A MEF2B MEF2C MEF2D MYOD1 NFATC1 NFATC2 PIK3CA PIK3R1 PPP3CA PPP3CB PPP3CC SYT1 YWHAH
G2 CALM1 CALM2 CALM3 DLG4 GRIN1 GRIN2A GRIN2B GRIN2C GRIN2D NOS1 PPP3CA PPP3CB PPP3CC PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 SYT1
G3 ACACA ACAS2 ACAS2L ACAT1 ACAT2 ACYP1 ACYP2 ADH5 AKR1B1 ALDH1A1 ALDH1A2 ALDH1A3 ALDH1B1 ALDH2 ALDH3A1 ALDH3A2 ALDH9A1 CACH_1 DLAT DLD GLO1 GRHPR HAGH HAGHL LDHA LDHB LDHC LDHD MDH1 MDH2 ME1 ME2 ME3 PC PCK1 PDHA1 PDHA2 PDHB PKLR PKM2
G4 ADCY1 CALM1 CALM2 CALM3 CREB1 ELK1 FOS GNAI1 GNAQ GNAS GNB1 GNGT1 HRAS JUN MAP2K1 MAPK3 NFATC1 NFATC2 NFATC3 NFATC4 PLCG1 PPP3CA PPP3CB PPP3CC PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 RAF1 RPS6KA3 SYT1
G5 ADCY1 ADCY2 ADCY3 ADCY4 ADCY5 ADCY6 ADCY7 ADCY8 ADCY9 AKAP1 AKAP10 AKAP11 AKAP12 AKAP2 /// PALM2_AKAP2 AKAP3 AKAP4 AKAP5 AKAP6 AKAP7 AKAP8 AKAP9 ARHGEF1 CALM1 CALM2 CALM3 CHMP1B GNA11 GNA12 GNA13 GNA14 GNA15 GNAI2 GNAI3 GNAL GNAO1 GNAQ GNAZ GNB1 GNB2 GNB3 GNB5 GNG10 GNG10 /// LOC552891 GNG12 GNG13 GNG3 GNG4 GNG5 GNG7 GNGT1 GNGT2 HRAS IL18BP ITPR1 KCNJ3 KRAS MGC11266 NRAS PALM2 /// PALM2_AKAP2 PALM2_AKAP2 PDE1A PDE1B PDE1C PDE4A PDE4B PDE4C PDE4D PDE7A PDE7B PDE8A PDE8B PLCB3 PPP3CA PPP3CC PRKACA PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 PRKCD PRKCE PRKCG PRKCH PRKCI PRKCQ PRKCZ PRKD1 PRKD3 RHOA RRAS SARA1 SLC9A1 USP5 G6 CDK5 CDK5R1 CSNK1D DRD1 DRD2 GRM1 PLCB1 PPP1CA PPP1R1B PPP2CA PPP3CA PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B
G7 CALM1 CALM2 CALM3 CALML3 CALML6 CARKL CDIPT CDS1 CDS2 DGKA DGKB DGKD DGKE DGKG DGKH DGKI DGKQ DGKZ FN3K IMPA1 IMPA2 INPP1 INPP4A INPP4B INPP5A INPP5B INPP5D INPP5E INPPL1 ITGB1BP3 ITPK1 ITPKA ITPKB ITPR1 ITPR2 ITPR3 OCRL PI4KA PI4KB PIB5PA PIK3C2A PIK3C2B PIK3C2G PIK3C3 PIK3CA PIK3CB PIK3CD PIK3CG PIK3R1 PIK3R2 PIK3R3 PIK3R5 PIP4K2A PIP4K2B PIP4K2C PIP5K1A PIP5K1B PIP5K1C PIP5K3 PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCD3 PLCD4 PLCE1 PLCG1 PLCG2 PLCZ1 PRKCA PRKCB1 PRKCG PTEN PTPMT1 SKIP SYNJ1 SYNJ2
G8 AGT AGTR2 BDK CALM1 CALM2 CALM3 CAMK2A CAMK2B CAMK2D CAMK2G CDK5 F2 FYN GNA11 GNAI1 GNB1 GNGT1 GRB2 HRAS JAK2 MAP2K1 MAP2K2 MAPK1 MAPK14 MAPK3 MAPK8 MAPT MYLK PLCG1 PRKCA PRKCB1 PTK2B RAF1 SHC1 SOS1 STAT1 STAT3 STAT5A SYT1
G9 ABCC8 ADIPOQ CACNA1A CACNA1B CACNA1C CACNA1D CACNA1E CACNA1G FRAP1 GCK IKBKB INS INSR IRS1 IRS2 IRS4 KCNJ11 MAFA MAPK1 MAPK10 MAPK3 MAPK8 MAPK9 PDX1 PIK3CA PIK3CB PIK3CD PIK3CG PIK3R1 PIK3R2 PIK3R3 PIK3R5 PKLR PKM2 PRKCD PRKCE PRKCZ SLC2A2 SLC2A4 SOCS1 SOCS2 SOCS3 SOCS4 TNF
G10 CARKL FN3K IMPA1 IMPA2 INPP1 INPP4A INPP4B INPP5A INPP5B INPP5E INPPL1 IPMK ISYNA1 ITGB1BP3 ITPK1 ITPKA ITPKB MINPP1 MIOX OCRL PI4KA PI4KB PIB5PA PIK3C3 PIK3CA PIK3CB PIK3CD PIK3CG PIP4K2A PIP4K2B PIP4K2C PIP5K1A PIP5K1B PIP5K1C PIP5K3 PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCD3 PLCD4 PLCE1 PLCG1 PLCG2 PLCZ1 PTEN PTPMT1 SKIP SYNJ1 SYNJ2
G11 CALM1 CALM2 CALM3 CAMK1 CAMK1G CAMK2A CAMK2B CAMK2D CAMK2G CAMK4 ESRRA HDAC5 MEF2A MEF2B MEF2C MEF2D PPARA PPARGC1 PPP3CA PPP3CB PPP3CC SLC2A4 SYT1 YWHAH
G12 CALM1 CALM2 CALM3 CAMK1 CAMK1G ELK1 FPR1 GNA15 GNB1 GNGT1 HRAS MAP2K1 MAP2K2 MAP2K3 MAP2K6 MAP3K1 MAPK1 MAPK14 MAPK3 NCF1 NCF2 NFATC1 NFATC2 NFATC3 NFATC4 NFKB1 NFKBIA PAK1 PIK3C2G PLCB1 PPP3CA PPP3CB PPP3CC RAC1 RAF1 RELA SYT1 G13 ADCY3 ADRBK2 ARRB2 CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CLCA1 CLCA2 CLCA4 CNGA3 CNGA4 CNGB1 GNAL GUCA1A GUCA1B GUCA1C PDC PDE1C PRKACA PRKACB PRKACG PRKG1 PRKG2 PRKX PRKY
G14 ADCY1 ADCY8 ARAF ATF4 BRAF CACNA1C CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CAMK4 CHP CREBBP EP300 GNAQ GRIA1 GRIA2 GRIN1 GRIN2A GRIN2B GRIN2C GRIN2D GRM1 GRM5 HRAS ITPR1 ITPR2 ITPR3 KRAS MAP2K1 MAP2K2 MAPK1 MAPK3 NRAS PLCB1 PLCB2 PLCB3 PLCB4 PPP1CA PPP1CB PPP1CC PPP1R12A PPP1R1A PPP3CA PPP3CB PPP3CC PPP3R1 PPP3R2 PRKACA PRKACB PRKACG PRKCA PRKCB1 PRKCG PRKX PRKY RAF1 RAP1A RAP1B RAPGEF3 RPS6KA1 RPS6KA2 RPS6KA3 RPS6KA6
G15 ADCY1 ADCY2 ADCY3 ADCY4 ADCY5 ADCY6 ADCY7 ADCY8 ADCY9 ATF4 CACNA1C CACNA1D CACNA1F CACNA1S CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CDC42 CGA EGFR ELK1 FSHB GNA11 GNAQ GNAS GNRH1 GNRH2 GNRHR GRB2 HBEGF HRAS ITPR1 ITPR2 ITPR3 JUN KRAS LHB MAP2K1 MAP2K2 MAP2K3 MAP2K4 MAP2K6 MAP2K7 MAP3K1 MAP3K2 MAP3K3 MAP3K4 MAPK1 MAPK10 MAPK11 MAPK12 MAPK13 MAPK14 MAPK3 MAPK7 MAPK8 MAPK9 MMP14 MMP2 NRAS PLA2G10 PLA2G12A PLA2G12B PLA2G1B PLA2G2A PLA2G2D PLA2G2E PLA2G2F PLA2G3 PLA2G4A PLA2G5 PLA2G6 PLCB1 PLCB2 PLCB3 PLCB4 PLD1 PLD2 PRKACA PRKACB PRKACG PRKCA PRKCB1 PRKCD PRKX PRKY PTK2B RAF1 SOS1 SOS2 SRC G16 AACS ABAT ACADS ACAT1 ACAT2 ALDH1A1 ALDH1A2 ALDH1A3 ALDH1B1 ALDH2 ALDH3A1 ALDH3A2 ALDH5A1 ALDH9A1 BDH BUCS1 ECHS1 EHHADH GAD1 GAD2 HADHA HMGCL L2HGDH OXCT1 PDHA1 PDHA2 PDHB SDHB SDS
G17 ARHA CCL11 CCR3 CFL1 GNAQ GNAS GNB1 GNGT1 HRAS LIMK1 MAP2K1 MAPK1 MAPK3 MYL2 NOX1 PIK3C2G PLCB1 PPP1R12B PRKCA PRKCB1 PTK2 RAF1 ROCK2
G18 ATP5E ATP5O ATP6AP1 ATP6V0A1 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0C /// SHMT1 ATP6V0D1 ATP6V0E ATP6V1A ATP6V1B1 ATP6V1B2 ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H FDXR
G19 BCAR1 CALM1 CALM2 CALM3 CRKL GNAQ GRB2 HRAS JUN MAP2K1 MAP2K2 MAP2K3 MAP2K4 MAP3K1 MAPK1 MAPK14 MAPK3 MAPK8 PAK1 PLCG1 PRKCA PRKCB1 PTK2B RAC1 RAF1 SHC1 SOS1 SRC SYT1
G20 ADRA1A ADRA1B ADRA1D ADRA2A ADRA2C ADRB1 ADRB2 ADRB3 CHRM1 CHRM2 CHRM3 CHRM4 CHRM5 DRD1 DRD2 DRD3 DRD4 DRD5 HRH1 HRH2 HTR1A HTR1B HTR1D HTR1E HTR1F HTR2A HTR2B HTR2C HTR4 HTR5A HTR6 HTR7 HTR7 /// LOC93164
G21 ACTA1 AGT AKT1 CALM1 CALM2 CALM3 CALR CAMK1 CAMK1G CAMK4 CREBBP CSNK1A1 CTF1 DTR EDN1 ELSPBP1 F2 FGF2 FKBP1A GATA4 GSK3B HAND1 HAND2 HRAS IGF1 LIF MAP2K1 MAPK1 MAPK14 MAPK3 MAPK8 MEF2C MYH2 NFATC1 NFATC2 NFATC3 NFATC4 NKX2-5 NPPA PIK3CA PIK3R1 PPP3CA PPP3CB PPP3CC PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B RAF1 RPS6KB1 SYT1
G22 AGT AGTR1 ATF2 CALM1 CALM2 CALM3 EGFR ELK1 GNAQ GRB2 HRAS JUN MAP2K1 MAP2K2 MAP2K4 MAP3K1 MAPK1 MAPK3 MAPK8 MEF2A MEF2B MEF2C MEF2D PAK1 PRKCA PRKCB1 PTK2 PTK2B RAC1 RAF1 SHC1 SOS1 SRC SYT1
G23 ACVR1 ACVR1B ACVRL1 AKT1 AURKB BMPR1A BMPR2 BUB1 CDC2L5 CDIPT CDKL1 CDKL2 CDS1 CDS2 CLK1 CLK2 CLK4 COL4A3BP CSNK2A1 CSNK2A1 /// CSNK2A1P CSNK2A2 CSNK2B DGKA DGKB DGKD DGKE DGKG DGKH DGKQ DGKZ IMPA1 INPP1 INPP4A INPP4B INPP5A INPPL1 ITPKA ITPKB MAP3K10 MOS NEK1 NEK3 OCRL PAK4 PCTK1 PCTK2 PIK3C2A PIK3C2B PIK3C2G PIK3CA PIK3CB PIK3CG PIK4CA PIK4CA /// LOC220686 PIM2 PIP5K2B PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCG1 PLCG2 PLK3 PRKACA PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 PRKCD PRKCE PRKCG PRKCH PRKCQ PRKCZ PRKD1 PRKG1 RAF1 RPS6KA1 RPS6KA2 RPS6KA3 RPS6KA4 RPS6KB1 STK11 TGFBR1 VRK1 G24 AMPH AP2A1 AP2M1 BIN1 CALM1 CALM2 CALM3 DNM1 EPN1 EPS15 NME1 NME2 PICALM PPP3CA PPP3CB PPP3CC SYNJ1 SYNJ2 SYT1
G25 ARAF BRAF C7orf16 CACNA1A CRH CRHR1 GNA11 GNA12 GNA13 GNAI1 GNAI2 GNAI3 GNAO1 GNAQ GNAS GNAZ GRIA1 GRIA2 GRIA3 GRID2 GRM1 GRM5 GUCY1A2 GUCY1A3 GUCY1B3 GUCY2C GUCY2D GUCY2F HRAS IGF1 IGF1R ITPR1 ITPR2 ITPR3 KRAS LYN MAP2K1 MAP2K2 MAPK1 MAPK3 NOS1 NOS2A NOS3 NPR1 NPR2 NRAS PLA2G10 PLA2G12A PLA2G12B PLA2G1B PLA2G2A PLA2G2D PLA2G2E PLA2G2F PLA2G3 PLA2G4A PLA2G5 PLA2G6 PLCB1 PLCB2 PLCB3 PLCB4 PPP2CA PPP2CB PPP2R1A PPP2R1B PPP2R2A PPP2R2B PPP2R2C PRKCA PRKCB1 PRKCG PRKG1 PRKG2 RAF1 RYR1
G26 ADCY1 AKT1 CAMK2A CAMK2B CAMK2D CAMK2G CREB1 GNAS GRB2 HRAS MAPK1 MAPK14 MAPK3 PIK3CA PIK3R1 PRKACB PRKACG PRKAR1A PRKAR1B PRKAR2A PRKAR2B PRKCA PRKCB1 RAC1 RPS6KA1 RPS6KA5 SOS1
G27 AACS AADAC ABAT ACADS ACAT1 ACAT2 ACSM1 AKR1B10 ALDH1A3 ALDH1B1 ALDH2 ALDH3A1 ALDH3A2 ALDH5A1 ALDH7A1 ALDH9A1 BDH1 BDH2 DDHD1 ECHS1 EHHADH GAD1 GAD2 HADH HADHA HMGCL HMGCS1 HMGCS2 HSD17B10 HSD17B4 HSD3B7 ILVBL L2HGDH OXCT1 OXCT2 PDHA1 PDHA2 PDHB PLA1A PPME1 PRDX6 RDH11 RDH12 RDH13 RDH14
G28 ALDOA ALDOB ALDOC FBP1 FBP2 GOT1 GOT2 GPT GPT2 MDH1 MDH2 ME1 ME2 ME3 PGK1 PKLR PKM2 RPE RPE /// LOC440001 RPIA TKT TPI1
G29 IMPA1 INPP1 INPP4A INPP4B INPP5A INPPL1 ITPKA ITPKB MIOX OCRL PIK3C2A PIK3C2B PIK3C2G PIK3CA PIK3CB PIK3CG PIK4CA PIK4CA_///_LOC220686 PIP5K2B PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCG1 PLCG2
G30 ATP5E ATP5O ATP6AP1 ATP6V0A1 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0C /// SHMT1 ATP6V0D1 ATP6V0E ATP6V1A ATP6V1B1 ATP6V1B2 ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H
G31 BF CAMK2A CAMK2B CAMK2D CAMK2G DAG1 ITPKA ITPKB ITPR1 ITPR2 ITPR3 NFAT5 PDE6A PDE6B PDE6C PDE6D PDE6G PDE6H SLC6A13 TF Table S6 ClickTable.htm here to download Table: Table S6.pdf 2/24/11 12:50 PM
Table S6. Canonical pathways associated with tumor or normal samples in GSAA-SNP (glioblastoma) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 HSA04720_LONG_TERM_POTENTIATION 56 0.0205 1 1 G2 FRUCTOSE_AND_MANNOSE_METABOLISM 21 0.0252 1 0.9707 G3 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES 30 0.0566 1 1 G4 CELLCYCLEPATHWAY 19 0.0709 1 0.9994 G5 SPPAPATHWAY 18 0.0998 1 0.9999 G6 ST_GA12_PATHWAY 21 0.1002 1 1 G7 INTRINSICPATHWAY 20 0.1019 1 1 G8 SIG_INSULIN_RECEPTOR_PATHWAY_IN_CARDIAC_MYO43 0.1028 1 1 G9 ST_ADRENERGIC 31 0.1073 1 1 G10 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY 30 0.1392 1 1 G11 HSA04730_LONG_TERM_DEPRESSION 67 0.1447 1 1 G12 KERATINOCYTEPATHWAY 34 0.1479 1 1 G13 METPATHWAY 30 0.1566 1 1 G14 PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 73 0.1576 1 1 G15 VEGFPATHWAY 25 0.1601 1 1 G16 HSA04070_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTE61 0.1607 1 1 G17 IL7PATHWAY 15 0.1609 1 1 G18 ST_G_ALPHA_I_PATHWAY 33 0.1673 1 1 G19 SIG_BCR_SIGNALING_PATHWAY 39 0.1841 1 1 G20 ST_WNT_CA2_CYCLIC_GMP_PATHWAY 18 0.1897 1 1 G21 GLYCEROPHOSPHOLIPID_METABOLISM 40 0.2106 1 1 G22 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_CHEMOTAXIS27 0.2135 1 1 G23 PGC1APATHWAY 22 0.2147 1 1 G24 HSA04930_TYPE_II_DIABETES_MELLITUS 33 0.217 1 1 G25 SA_B_CELL_RECEPTOR_COMPLEXES 22 0.2345 1 1 G26 CXCR4PATHWAY 19 0.2487 1 1 G27 BCRPATHWAY 30 0.2489 1 1 G28 INOSITOL_PHOSPHATE_METABOLISM 21 0.2489 1 1 G29 FCER1PATHWAY 33 0.2508 1 1 G30 HSA00565_ETHER_LIPID_METABOLISM 24 0.2643 1 1 G31 NOS1PATHWAY 19 0.2692 1 1 G32 HSA00051_FRUCTOSE_AND_MANNOSE_METABOLISM 33 0.2786 1 1 G33 CALCINEURINPATHWAY 16 0.302 1 1 G34 SIG_PIP3_SIGNALING_IN_CARDIAC_MYOCTES 52 0.3057 1 1 G35 HSA00564_GLYCEROPHOSPHOLIPID_METABOLISM 47 0.3102 1 1 G36 HSA03030_DNA_POLYMERASE 18 0.3147 1 1 G37 G_PROTEIN_SIGNALING 74 0.3177 1 1 G38 G2PATHWAY 21 0.3232 1 1 G39 FMLPPATHWAY 32 0.3289 1 1 G40 ATMPATHWAY 17 0.3346 1 1 G41 HSA04662_B_CELL_RECEPTOR_SIGNALING_PATHWAY 49 0.3379 1 1 G42 INTEGRINPATHWAY 30 0.3432 1 1 G43 NO1PATHWAY 25 0.3477 1 1 G44 PTDINSPATHWAY 19 0.348 1 1 G45 HSA04916_MELANOGENESIS 71 0.3568 1 1 G46 HSA00591_LINOLEIC_ACID_METABOLISM 26 0.3635 1 1 G47 HSA00562_INOSITOL_PHOSPHATE_METABOLISM 37 0.3714 1 1 G48 TRYPTOPHAN_METABOLISM 46 0.3747 1 1 G49 HSA02010_ABC_TRANSPORTERS_GENERAL 33 0.3839 1 1 G50 GALACTOSE_METABOLISM 19 0.3997 1 1 G51 HSA00360_PHENYLALANINE_METABOLISM 24 0.4065 1 1 G52 HSA05217_BASAL_CELL_CARCINOMA 36 0.4077 1 1 G53 HDACPATHWAY 27 0.412 1 1 G54 HSA00030_PENTOSE_PHOSPHATE_PATHWAY 23 0.4122 1 1 G55 ST_MYOCYTE_AD_PATHWAY 21 0.414 1 1 G56 HSA04370_VEGF_SIGNALING_PATHWAY 58 0.4227 1 1 G57 GLYCEROLIPID_METABOLISM 36 0.4305 1 1 G58 P53PATHWAY 15 0.4399 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 6 Table.htm 2/24/11 12:50 PM
G59 HSA04664_FC_EPSILON_RI_SIGNALING_PATHWAY 64 0.4405 1 1 G60 ST_B_CELL_ANTIGEN_RECEPTOR 37 0.4557 1 1 G61 HSA04320_DORSO_VENTRAL_AXIS_FORMATION 22 0.4571 1 1 G62 PHENYLALANINE_METABOLISM 19 0.459 1 1 G63 HSA00534_HEPARAN_SULFATE_BIOSYNTHESIS 16 0.4654 1 1 G64 HSA04520_ADHERENS_JUNCTION 68 0.4662 1 1 G65 SPRYPATHWAY 15 0.4674 1 1 G66 HSA00052_GALACTOSE_METABOLISM 24 0.4686 1 1 G67 PROSTAGLANDIN_AND_LEUKOTRIENE_METABOLISM 27 0.4698 1 1 G68 PENTOSE_PHOSPHATE_PATHWAY 21 0.4706 1 1 G69 RIBOSOMAL_PROTEINS 55 0.4728 1 1 G70 HSA04912_GNRH_SIGNALING_PATHWAY 80 0.4775 1 1 G71 HSA00220_UREA_CYCLE_AND_METABOLISM_OF_AMIN24 0.4792 1 1 G72 TOLLPATHWAY 27 0.4835 1 1 G73 HSA05030_AMYOTROPHIC_LATERAL_SCLEROSIS 15 0.4865 1 1 G74 HSA00590_ARACHIDONIC_ACID_METABOLISM 41 0.4879 1 1 G75 MEF2DPATHWAY 16 0.4884 1 1 G76 HSA01032_GLYCAN_STRUCTURES_DEGRADATION 21 0.4925 1 1 G77 CCR3PATHWAY 19 0.4931 1 1 G78 BLOOD_CLOTTING_CASCADE 18 0.5018 1 1 G79 HSA04740_OLFACTORY_TRANSDUCTION 23 0.505 1 1 G80 WNT_SIGNALING 46 0.5132 1 1 G81 BUTANOATE_METABOLISM 24 0.5167 1 1 G82 HSA05214_GLIOMA 58 0.5306 1 1 G83 RACCYCDPATHWAY 19 0.5383 1 1 G84 NFATPATHWAY 42 0.5398 1 1 G85 TCRPATHWAY 37 0.553 1 1 G86 GHPATHWAY 21 0.5565 1 1 G87 ERK5PATHWAY 16 0.5567 1 1 G88 HSA00512_O_GLYCAN_BIOSYNTHESIS 18 0.5627 1 1 G89 IL2RBPATHWAY 28 0.5683 1 1 G90 HSA00632_BENZOATE_DEGRADATION_VIA_COA_LIGAT20 0.5694 1 1 G91 HSA00600_SPHINGOLIPID_METABOLISM 25 0.5706 1 1 G92 HSA04512_ECM_RECEPTOR_INTERACTION 74 0.5839 1 1 G93 CERAMIDEPATHWAY 16 0.589 1 1 G94 HSA05223_NON_SMALL_CELL_LUNG_CANCER 50 0.5998 1 1 G95 HSA04012_ERBB_SIGNALING_PATHWAY 77 0.6023 1 1 G96 HSA05130_PATHOGENIC_ESCHERICHIA_COLI_INFECTIO33 0.6032 1 1 G97 HSA05131_PATHOGENIC_ESCHERICHIA_COLI_INFECTIO33 0.6032 1 1 G98 CARM_ERPATHWAY 25 0.6067 1 1 G99 VIPPATHWAY 21 0.6091 1 1 G100 NKCELLSPATHWAY 16 0.6095 1 1 G101 GPCRDB_OTHER 39 0.6105 1 1 G102 HSA04340_HEDGEHOG_SIGNALING_PATHWAY 38 0.6118 1 1 G103 GPCRPATHWAY 29 0.6225 1 1 G104 INTEGRIN_MEDIATED_CELL_ADHESION_KEGG 81 0.6338 1 1 G105 ATRBRCAPATHWAY 19 0.6467 1 1 G106 HISTIDINE_METABOLISM 22 0.6514 1 1 G107 GLUTATHIONE_METABOLISM 24 0.655 1 1 G108 NDKDYNAMINPATHWAY 16 0.6593 1 1 G109 NUCLEAR_RECEPTORS 37 0.66 1 1 G110 STARCH_AND_SUCROSE_METABOLISM 27 0.6644 1 1 G111 IGF1PATHWAY 18 0.6718 1 1 G112 BIOPEPTIDESPATHWAY 36 0.6736 1 1 G113 ST_GAQ_PATHWAY 25 0.6744 1 1 G114 ST_ERK1_ERK2_MAPK_PATHWAY 24 0.675 1 1 G115 TIDPATHWAY 15 0.6764 1 1 G116 EIF4PATHWAY 20 0.6825 1 1 G117 GLYCOLYSIS_AND_GLUCONEOGENESIS 38 0.6829 1 1 G118 HSA04540_GAP_JUNCTION 70 0.6846 1 1 G119 PAR1PATHWAY 18 0.6883 1 1 G120 TYROSINE_METABOLISM 24 0.6884 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 6 Table.htm 2/24/11 12:50 PM
G121 AT1RPATHWAY 32 0.6898 1 1 G122 GLYCOSPHINGOLIPID_METABOLISM 19 0.6941 1 1 G123 RHOPATHWAY 27 0.6994 1 1 G124 HSA00710_CARBON_FIXATION 19 0.6998 1 1 G125 HSA00410_BETA_ALANINE_METABOLISM 23 0.7031 1 1 G126 SA_PTEN_PATHWAY 15 0.7033 1 1 G127 HSA00650_BUTANOATE_METABOLISM 39 0.7083 1 1 G128 HSA05219_BLADDER_CANCER 36 0.7134 1 1 G129 HSA00561_GLYCEROLIPID_METABOLISM 42 0.7274 1 1 G130 HSA00903_LIMONENE_AND_PINENE_DEGRADATION 23 0.7277 1 1 G131 HSA05040_HUNTINGTONS_DISEASE 26 0.7315 1 1 G132 IL2PATHWAY 19 0.7329 1 1 G133 HSA05050_DENTATORUBROPALLIDOLUYSIAN_ATROPHY15 0.736 1 1 G134 PYK2PATHWAY 25 0.738 1 1 G135 ECMPATHWAY 19 0.7385 1 1 G136 INSULINPATHWAY 18 0.7423 1 1 G137 GPCRDB_CLASS_B_SECRETIN_LIKE 19 0.7487 1 1 G138 CARBON_FIXATION 19 0.7551 1 1 G139 HSA04150_MTOR_SIGNALING_PATHWAY 38 0.7639 1 1 G140 SIG_IL4RECEPTOR_IN_B_LYPHOCYTES 24 0.7674 1 1 G141 HSA05216_THYROID_CANCER 27 0.7701 1 1 G142 HSA04650_NATURAL_KILLER_CELL_MEDIATED_CYTOTO95 0.7702 1 1 G143 RNA_TRANSCRIPTION_REACTOME 24 0.7717 1 1 G144 ARGININE_AND_PROLINE_METABOLISM 36 0.7767 1 1 G145 ST_FAS_SIGNALING_PATHWAY 47 0.7768 1 1 G146 EPOPATHWAY 16 0.7795 1 1 G147 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS 34 0.7908 1 1 G148 OVARIAN_INFERTILITY_GENES 21 0.7967 1 1 G149 ST_INTERLEUKIN_4_PATHWAY 24 0.8002 1 1 G150 TPOPATHWAY 20 0.8028 1 1 G151 MCALPAINPATHWAY 18 0.8039 1 1 G152 HSA04920_ADIPOCYTOKINE_SIGNALING_PATHWAY 57 0.8041 1 1 G153 UBIQUITIN_MEDIATED_PROTEOLYSIS 16 0.8082 1 1 G154 GLEEVECPATHWAY 19 0.8084 1 1 G155 HSA00340_HISTIDINE_METABOLISM 33 0.811 1 1 G156 HSA05213_ENDOMETRIAL_CANCER 48 0.8134 1 1 G157 NGFPATHWAY 16 0.8137 1 1 G158 BETA_ALANINE_METABOLISM 24 0.8139 1 1 G159 HSA00380_TRYPTOPHAN_METABOLISM 47 0.8151 1 1 G160 HSA04610_COMPLEMENT_AND_COAGULATION_CASCA61 0.8203 1 1 G161 G1PATHWAY 24 0.8209 1 1 G162 HSA04742_TASTE_TRANSDUCTION 23 0.8243 1 1 G163 IGF1MTORPATHWAY 19 0.8306 1 1 G164 N_GLYCAN_BIOSYNTHESIS 20 0.831 1 1 G165 RASPATHWAY 18 0.8322 1 1 G166 P53HYPOXIAPATHWAY 16 0.8325 1 1 G167 EDG1PATHWAY 19 0.8327 1 1 G168 ERKPATHWAY 27 0.8348 1 1 G169 HSA00640_PROPANOATE_METABOLISM 29 0.8348 1 1 G170 ST_GA13_PATHWAY 32 0.8349 1 1 G171 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS 29 0.8367 1 1 G172 HSA00510_N_GLYCAN_BIOSYNTHESIS 30 0.8409 1 1 G173 HSA00330_ARGININE_AND_PROLINE_METABOLISM 25 0.8448 1 1 G174 GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 23 0.845 1 1 G175 HSA00010_GLYCOLYSIS_AND_GLUCONEOGENESIS 49 0.845 1 1 G176 GLUCONEOGENESIS 45 0.8483 1 1 G177 GLYCOLYSIS 45 0.8483 1 1 G178 EGFPATHWAY 24 0.8493 1 1 G179 PROSTAGLANDIN_SYNTHESIS_REGULATION 23 0.8529 1 1 G180 ST_INTEGRIN_SIGNALING_PATHWAY 70 0.8535 1 1 G181 HSA00563_GLYCOSYLPHOSPHATIDYLINOSITOL_ANCHO 17 0.8539 1 1 G182 HSA00602_GLYCOSPHINGOLIPID_BIOSYNTHESIS_NEO_L16 0.8555 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 6 Table.htm 2/24/11 12:50 PM
G183 SIG_CHEMOTAXIS 41 0.8559 1 1 G184 RAC1PATHWAY 22 0.8569 1 1 G185 PDGFPATHWAY 23 0.8572 1 1 G186 IL6PATHWAY 18 0.8576 1 1 G187 HSA04670_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATI 90 0.858 1 1 G188 HSA04614_RENIN_ANGIOTENSIN_SYSTEM 15 0.8602 1 1 G189 MONOAMINE_GPCRS 21 0.8604 1 1 G190 HSA04115_P53_SIGNALING_PATHWAY 51 0.8618 1 1 G191 ST_T_CELL_SIGNAL_TRANSDUCTION 41 0.8649 1 1 G192 HSA05220_CHRONIC_MYELOID_LEUKEMIA 69 0.866 1 1 G193 BADPATHWAY 20 0.8665 1 1 G194 CREBPATHWAY 23 0.8681 1 1 G195 HSA00350_TYROSINE_METABOLISM 43 0.8707 1 1 G196 DNA_REPLICATION_REACTOME 38 0.872 1 1 G197 STRIATED_MUSCLE_CONTRACTION 31 0.872 1 1 G198 HSA05221_ACUTE_MYELOID_LEUKEMIA 43 0.8722 1 1 G199 HSA04140_REGULATION_OF_AUTOPHAGY 21 0.8746 1 1 G200 HSA05218_MELANOMA 62 0.8819 1 1 G201 HSA00760_NICOTINATE_AND_NICOTINAMIDE_METAB 15 0.8884 1 1 G202 PURINE_METABOLISM 92 0.8942 1 1 G203 BREAST_CANCER_ESTROGEN_SIGNALING 80 0.8965 1 1 G204 HSA04130_SNARE_INTERACTIONS_IN_VESICULAR_TRA 27 0.8989 1 1 G205 ST_GRANULE_CELL_SURVIVAL_PATHWAY 21 0.9043 1 1 G206 GLUTAMATE_METABOLISM 22 0.9047 1 1 G207 SA_TRKA_RECEPTOR 15 0.9078 1 1 G208 CELL_CYCLE_KEGG 74 0.908 1 1 G209 HSA00251_GLUTAMATE_METABOLISM 27 0.9084 1 1 G210 TNFR2PATHWAY 15 0.9107 1 1 G211 ANDROGEN_AND_ESTROGEN_METABOLISM 19 0.9151 1 1 G212 NTHIPATHWAY 19 0.9184 1 1 G213 G1_TO_S_CELL_CYCLE_REACTOME 53 0.9222 1 1 G214 HSA05222_SMALL_CELL_LUNG_CANCER 77 0.9222 1 1 G215 HSA00530_AMINOSUGARS_METABOLISM 24 0.9264 1 1 G216 PROPANOATE_METABOLISM 28 0.9295 1 1 G217 HSA04660_T_CELL_RECEPTOR_SIGNALING_PATHWAY 81 0.9296 1 1 G218 HSA00620_PYRUVATE_METABOLISM 34 0.93 1 1 G219 PPARAPATHWAY 38 0.9301 1 1 G220 HSA01510_NEURODEGENERATIVE_DISEASES 33 0.9308 1 1 G221 HSA05211_RENAL_CELL_CARCINOMA 64 0.9313 1 1 G222 HSA04640_HEMATOPOIETIC_CELL_LINEAGE 65 0.9314 1 1 G223 NITROGEN_METABOLISM 20 0.9316 1 1 G224 PYRUVATE_METABOLISM 32 0.9351 1 1 G225 AMINOACYL_TRNA_BIOSYNTHESIS 19 0.9366 1 1 G226 HSA00910_NITROGEN_METABOLISM 23 0.9386 1 1 G227 GCRPATHWAY 16 0.9404 1 1 G228 ST_JNK_MAPK_PATHWAY 37 0.9421 1 1 G229 AMIPATHWAY 18 0.9424 1 1 G230 CSKPATHWAY 18 0.9424 1 1 G231 HSA00500_STARCH_AND_SUCROSE_METABOLISM 53 0.943 1 1 G232 CIRCADIAN_EXERCISE 35 0.9455 1 1 G233 IL1RPATHWAY 26 0.9465 1 1 G234 HSA05215_PROSTATE_CANCER 77 0.9476 1 1 G235 GSK3PATHWAY 21 0.9479 1 1 G236 FASPATHWAY 24 0.948 1 1 G237 BILE_ACID_BIOSYNTHESIS 21 0.9487 1 1 G238 HSA05010_ALZHEIMERS_DISEASE 22 0.9492 1 1 G239 STRESSPATHWAY 18 0.9508 1 1 G240 41BBPATHWAY 17 0.9518 1 1 G241 ST_WNT_BETA_CATENIN_PATHWAY 23 0.9549 1 1 G242 HSA03010_RIBOSOME 34 0.9551 1 1 G243 CHEMICALPATHWAY 19 0.9554 1 1 G244 HSA01030_GLYCAN_STRUCTURES_BIOSYNTHESIS_1 74 0.9581 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 6 Table.htm 2/24/11 12:50 PM
G245 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWA80 0.9583 1 1 G246 INFLAMPATHWAY 21 0.9583 1 1 G247 DCPATHWAY 15 0.9602 1 1 G248 HSA00240_PYRIMIDINE_METABOLISM 58 0.9616 1 1 G249 TOB1PATHWAY 15 0.9646 1 1 G250 PEPTIDE_GPCRS 56 0.9648 1 1 G251 HSA00450_SELENOAMINO_ACID_METABOLISM 21 0.966 1 1 G252 HSA05210_COLORECTAL_CANCER 69 0.966 1 1 G253 CTLA4PATHWAY 16 0.9667 1 1 G254 SIG_REGULATION_OF_THE_ACTIN_CYTOSKELETON_BY_32 0.9671 1 1 G255 HSA01430_CELL_COMMUNICATION 93 0.9673 1 1 G256 HSA00970_AMINOACYL_TRNA_BIOSYNTHESIS 25 0.9694 1 1 G257 HSA00071_FATTY_ACID_METABOLISM 36 0.9701 1 1 G258 MAPKPATHWAY 74 0.9707 1 1 G259 NFKBPATHWAY 18 0.9726 1 1 G260 HSA05212_PANCREATIC_CANCER 66 0.975 1 1 G261 IL12PATHWAY 17 0.976 1 1 G262 GLYCINE_SERINE_AND_THREONINE_METABOLISM 29 0.9768 1 1 G263 HSA04330_NOTCH_SIGNALING_PATHWAY 31 0.977 1 1 G264 TNFR1PATHWAY 24 0.9775 1 1 G265 HSA00150_ANDROGEN_AND_ESTROGEN_METABOLISM35 0.9789 1 1 G266 P38MAPKPATHWAY 34 0.979 1 1 G267 ALANINE_AND_ASPARTATE_METABOLISM 18 0.9802 1 1 G268 LYSINE_DEGRADATION 26 0.9806 1 1 G269 HSA00252_ALANINE_AND_ASPARTATE_METABOLISM 27 0.981 1 1 G270 CHOLESTEROL_BIOSYNTHESIS 15 0.9812 1 1 G271 APOPTOSIS_GENMAPP 33 0.9814 1 1 G272 HSA00260_GLYCINE_SERINE_AND_THREONINE_METAB33 0.9815 1 1 G273 HSA05120_EPITHELIAL_CELL_SIGNALING_IN_HELICOBA56 0.9821 1 1 G274 CALCINEURIN_NF_AT_SIGNALING 73 0.9826 1 1 G275 ST_P38_MAPK_PATHWAY 31 0.9826 1 1 G276 HSA04110_CELL_CYCLE 90 0.9827 1 1 G277 SIG_CD40PATHWAYMAP 27 0.9833 1 1 G278 VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 33 0.9834 1 1 G279 HSA00790_FOLATE_BIOSYNTHESIS 31 0.9851 1 1 G280 HSA00120_BILE_ACID_BIOSYNTHESIS 29 0.9855 1 1 G281 TH1TH2PATHWAY 17 0.986 1 1 G282 MPRPATHWAY 19 0.9862 1 1 G283 HSA00980_METABOLISM_OF_XENOBIOTICS_BY_CYTOC40 0.9868 1 1 G284 HSA01031_GLYCAN_STRUCTURES_BIOSYNTHESIS_2 47 0.9878 1 1 G285 HSA05110_CHOLERA_INFECTION 32 0.9883 1 1 G286 ALKPATHWAY 25 0.9908 1 1 G287 HIVNEFPATHWAY 45 0.9912 1 1 G288 HSA00361_GAMMA_HEXACHLOROCYCLOHEXANE_DEG19 0.9914 1 1 G289 CYTOKINEPATHWAY 15 0.9915 1 1 G290 APOPTOSIS_KEGG 39 0.993 1 1 G291 HSA04210_APOPTOSIS 66 0.9932 1 1 G292 MTORPATHWAY 22 0.9942 1 1 G293 HSA00310_LYSINE_DEGRADATION 38 0.9945 1 1 G294 HSA00100_BIOSYNTHESIS_OF_STEROIDS 22 0.9947 1 1 G295 HSA03022_BASAL_TRANSCRIPTION_FACTORS 23 0.9949 1 1 G296 MITOCHONDRIAPATHWAY 16 0.9949 1 1 G297 TRANSLATION_FACTORS 31 0.9956 1 1 G298 ATP_SYNTHESIS 17 0.9959 1 1 G299 FLAGELLAR_ASSEMBLY 17 0.9959 1 1 G300 PHOTOSYNTHESIS 18 0.9959 1 1 G301 TYPE_III_SECRETION_SYSTEM 17 0.9959 1 1 G302 DEATHPATHWAY 25 0.9961 1 1 G303 HSA03320_PPAR_SIGNALING_PATHWAY 57 0.9963 1 1 G304 HSA00020_CITRATE_CYCLE 23 0.9964 1 1 G305 CITRATE_CYCLE_TCA_CYCLE 18 0.9969 1 1 G306 WNTPATHWAY 19 0.997 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 5 of 6 Table.htm 2/24/11 12:50 PM
G307 MRNA_PROCESSING_REACTOME 82 0.9971 1 1 G308 APOPTOSIS 52 0.9975 1 1 G309 PYRIMIDINE_METABOLISM 45 0.9981 1 1 G310 HSA04940_TYPE_I_DIABETES_MELLITUS 33 0.9985 1 1 G311 CASPASEPATHWAY 19 0.9986 1 1 G312 HSA00280_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRA42 0.9988 1 1 G313 HSA04350_TGF_BETA_SIGNALING_PATHWAY 67 0.9989 1 1 G314 ST_TUMOR_NECROSIS_FACTOR_PATHWAY 23 0.9991 1 1 G315 HSA00480_GLUTATHIONE_METABOLISM 26 0.9993 1 1 G316 KREBS_TCA_CYCLE 25 0.9993 1 1 G317 NKTPATHWAY 21 0.9995 1 1 G318 HSA00190_OXIDATIVE_PHOSPHORYLATION 81 1 1 1 G319 HSA00860_PORPHYRIN_AND_CHLOROPHYLL_METABOL20 1 1 1 G320 HSA03050_PROTEASOME 20 1 1 1 G321 HSA04612_ANTIGEN_PROCESSING_AND_PRESENTATIO49 1 1 1 G322 OXIDATIVE_PHOSPHORYLATION 46 1 1 1 G323 PROTEASOMEPATHWAY 17 1 1 1
Note: Software GSAA-SNP (version 1.0) won't report gene sets with a negative AS score because negative scores are not biologically meaningful in GSAA-SNP.
file:///Users/sayan/Desktop/Qing/Table.htm Page 6 of 6 Table S7 ClickTable.htm here to download Table: Table S7.pdf 2/24/11 1:09 PM
Table S7. Canonical pathways associated with tumor samples in GSEAndes (Glioblastoma) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 RIBOSOMAL_PROTEINS 81 0.15844233 0.34398633 0.3931 G2 PROTEASOME 16 0.024422346 0.36597782 0.2321 G3 APOPTOSIS 66 0.04038344 0.4848573 1 G4 HSA00240_PYRIMIDINE_METABOLISM 70 0.08681607 0.48683423 1 G5 HSP27PATHWAY 15 0.17664552 0.4890643 1 G6 INTRINSICPATHWAY 22 0.1195546 0.48955375 1 G7 ST_ERK1_ERK2_MAPK_PATHWAY 29 0.106542796 0.49049166 1 G8 HSA05216_THYROID_CANCER 29 0.09242073 0.4907232 1 G9 G1_TO_S_CELL_CYCLE_REACTOME 61 0.107350096 0.4910395 1 G10 ST_FAS_SIGNALING_PATHWAY 59 0.026310736 0.4914779 1 G11 G2PATHWAY 23 0.07395874 0.4917297 1 G12 HSA03030_DNA_POLYMERASE 21 0.17650555 0.49485895 1 G13 CERAMIDEPATHWAY 22 0.001419015 0.4955514 0.8647 G14 MCALPAINPATHWAY 22 0.063782245 0.50134444 0.9975 G15 HSA00500_STARCH_AND_SUCROSE_META 59 0.06509357 0.50197613 1 G16 PROSTAGLANDIN_SYNTHESIS_REGULATION27 0.035622403 0.51396334 1 G17 HSA05050_DENTATORUBROPALLIDOLUYSI 15 0.1773913 0.5183694 1 G18 HSA05210_COLORECTAL_CANCER 81 0.03874092 0.5192157 1 G19 IL6PATHWAY 21 0.13412079 0.5192586 1 G20 CHEMICALPATHWAY 21 0.06869773 0.5216523 1 G21 CASPASEPATHWAY 22 0.09225767 0.5251823 1 G22 TNFR1PATHWAY 28 0.005720123 0.5260521 0.9898 G23 HSA05222_SMALL_CELL_LUNG_CANCER 87 0.05578343 0.52756727 1 G24 DEATHPATHWAY 32 0.10921705 0.52780324 1 G25 FASPATHWAY 27 0.010307153 0.52908456 0.9928 G26 ATMPATHWAY 19 0.07173601 0.52919024 1 G27 HSA05040_HUNTINGTONS_DISEASE 27 0.024293035 0.5293051 0.9975 G28 HCMVPATHWAY 15 0.18068357 0.5324497 1 G29 RACCYCDPATHWAY 22 0.08593594 0.53357536 1 G30 APOPTOSIS_GENMAPP 42 0.10796355 0.5337382 1 G31 CELLCYCLEPATHWAY 22 0.064902455 0.53523976 1 G32 HSA05221_ACUTE_MYELOID_LEUKEMIA 52 0.02862707 0.5358903 1 G33 NFKBPATHWAY 23 0.20933522 0.53616846 1 G34 HSA04610_COMPLEMENT_AND_COAGULA64 0.15197447 0.5377332 1 G35 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALI 97 0.1113929 0.5397377 1 G36 MTORPATHWAY 23 0.20723876 0.54013765 1 G37 TELPATHWAY 15 0.21586606 0.54148614 1 G38 CSKPATHWAY 20 0.14819685 0.5431773 0.9994 G39 HSA05010_ALZHEIMERS_DISEASE 24 0.042759962 0.54519755 1 G40 HSA04210_APOPTOSIS 78 0.032525253 0.5469211 1 G41 ECMPATHWAY 21 0.21846712 0.54888916 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 1:09 PM
G42 TIDPATHWAY 17 0.18220598 0.54973096 1 G43 TNFR2PATHWAY 18 0.071814366 0.54976946 0.9989 G44 P53PATHWAY 16 0.12979707 0.5518349 1 G45 HSA01032_GLYCAN_STRUCTURES_DEGRAD26 0.044413183 0.5547121 0.988 G46 APOPTOSIS_KEGG 48 0.048549682 0.555189 1 G47 IL3PATHWAY 15 0.2813354 0.55578446 1 G48 ATRBRCAPATHWAY 20 0.063206784 0.5590445 0.9987 G49 HSA04940_TYPE_I_DIABETES_MELLITUS 39 0.03510872 0.5619118 0.9974 G50 HSA04330_NOTCH_SIGNALING_PATHWAY 37 0.17313375 0.5632361 1 G51 HSA00860_PORPHYRIN_AND_CHLOROPHYL27 0.03208985 0.5666774 0.9844 G52 HYPERTROPHY_MODEL 19 0.1975 0.5668478 1 G53 HSA04120_UBIQUITIN_MEDIATED_PROTEO32 0.079877116 0.56725836 0.9968 G54 DNA_REPLICATION_REACTOME 43 0.18845165 0.56861496 1 G55 AMIPATHWAY 20 0.14819685 0.5690429 0.9994 G56 SPPAPATHWAY 20 0.03940404 0.5695704 0.9997 G57 STRESSPATHWAY 24 0.08866995 0.57433987 0.9999 G58 ST_P38_MAPK_PATHWAY 35 0.17467164 0.57679355 1 G59 CELL_CYCLE_KEGG 79 0.09049595 0.58051443 0.9997 G60 ST_TUMOR_NECROSIS_FACTOR_PATHWAY29 0.25656566 0.5811083 1 G61 VEGFPATHWAY 27 0.27267304 0.58207476 1 G62 STARCH_AND_SUCROSE_METABOLISM 29 0.012195122 0.58518994 0.9728 G63 PORPHYRIN_AND_CHLOROPHYLL_METABO18 0.0089268 0.58695346 0.8617 G64 UCALPAINPATHWAY 15 0.38112488 0.5870255 1 G65 TOLLPATHWAY 30 0.07883987 0.5875759 1 G66 HSA04612_ANTIGEN_PROCESSING_AND_P 73 0.15164924 0.5876507 1 G67 41BBPATHWAY 18 0.37618956 0.5881156 1 G68 HSA05212_PANCREATIC_CANCER 71 0.12135146 0.5882869 1 G69 G1PATHWAY 25 0.20023626 0.5890293 1 G70 HSA04115_P53_SIGNALING_PATHWAY 62 0.12665176 0.5905301 1 G71 STATIN_PATHWAY_PHARMGKB 16 0.25274056 0.59131634 1 G72 HIVNEFPATHWAY 54 0.16891192 0.59132487 1 G73 MITOCHONDRIAL_FATTY_ACID_BETAOXIDA15 0.36090663 0.59330046 1 G74 HSA04512_ECM_RECEPTOR_INTERACTION 80 0.19402693 0.5936645 1 G75 PYRIMIDINE_METABOLISM 55 0.20582727 0.5943389 1 G76 PROSTAGLANDIN_AND_LEUKOTRIENE_MET30 0.2704192 0.5957342 1 G77 HSA00531_GLYCOSAMINOGLYCAN_DEGRA16 0.046837945 0.59912574 0.9606 G78 HSA05220_CHRONIC_MYELOID_LEUKEMIA74 0.1506 0.6012649 1 G79 RELAPATHWAY 16 0.05756844 0.61028385 0.9831 G80 HSA01030_GLYCAN_STRUCTURES_BIOSYNT81 0.2044241 0.64245903 1 G81 INTEGRINPATHWAY 32 0.009758081 0.64445055 0.9516 G82 HSA05217_BASAL_CELL_CARCINOMA 45 0.25619346 0.66377217 1 G83 CTLA4PATHWAY 17 0.4174484 0.66602165 1 G84 CARDIACEGFPATHWAY 17 0.31570578 0.6679422 1 G85 UBIQUITIN_MEDIATED_PROTEOLYSIS 21 0.17056075 0.6707274 0.7396 G86 SPRYPATHWAY 16 0.38569078 0.69572175 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 1:09 PM
G87 HSA02010_ABC_TRANSPORTERS_GENERAL35 0.30463576 0.699527 1 G88 GALACTOSE_METABOLISM 22 0.3774926 0.70079535 1 G89 RASPATHWAY 22 0.013626041 0.72127116 0.8571 G90 NTHIPATHWAY 21 0.3971032 0.7267984 1 G91 HSA05213_ENDOMETRIAL_CANCER 50 0.3446396 0.7308448 1 G92 INTEGRIN_MEDIATED_CELL_ADHESION_KE83 0.34427208 0.7324298 1 G93 HSA00310_LYSINE_DEGRADATION 40 0.3569781 0.7325609 1 G94 IL1RPATHWAY 30 0.37778655 0.7328193 1 G95 GSK3PATHWAY 25 0.3803599 0.7353263 1 G96 P53HYPOXIAPATHWAY 18 0.42073643 0.74199116 1 G97 SA_CASPASE_CASCADE 16 0.4251274 0.7424908 1 G98 HSA05219_BLADDER_CANCER 41 0.3502994 0.7437599 1 G99 HSA00591_LINOLEIC_ACID_METABOLISM 27 0.5162363 0.7471299 1 G100 IL2RBPATHWAY 34 0.52488595 0.74850976 1 G101 HSA00450_SELENOAMINO_ACID_METABO 24 0.5260861 0.75156665 1 G102 HSA04670_LEUKOCYTE_TRANSENDOTHELI 100 0.38369587 0.75399554 1 G103 HSA00770_PANTOTHENATE_AND_COA_BI 15 0.53532934 0.75454587 1 G104 ARAPPATHWAY 20 0.5699864 0.75783527 1 G105 BREAST_CANCER_ESTROGEN_SIGNALING 91 0.63614094 0.75791943 1 G106 AKTPATHWAY 17 0.5268151 0.7590722 1 G107 IGF1MTORPATHWAY 20 0.46363637 0.75987583 1 G108 LAIRPATHWAY 15 0.58545744 0.7606239 1 G109 PITX2PATHWAY 16 0.5692972 0.7637177 1 G110 HSA05131_PATHOGENIC_ESCHERICHIA_CO41 0.5031092 0.76386595 1 G111 N_GLYCAN_BIOSYNTHESIS 21 0.46528178 0.76511973 1 G112 HSA00051_FRUCTOSE_AND_MANNOSE_M36 0.5469054 0.76686907 1 G113 HSA05215_PROSTATE_CANCER 84 0.5678221 0.7670481 1 G114 MITOCHONDRIAPATHWAY 20 0.45377645 0.7688852 1 G115 EICOSANOID_SYNTHESIS 16 0.5750145 0.76935226 1 G116 HSA05130_PATHOGENIC_ESCHERICHIA_CO41 0.5031092 0.770451 1 G117 HSA00760_NICOTINATE_AND_NICOTINAMI16 0.4998065 0.77121764 1 G118 HSA00510_N_GLYCAN_BIOSYNTHESIS 32 0.5134393 0.77182317 1 G119 HSA00530_AMINOSUGARS_METABOLISM 26 0.54984426 0.77225643 1 G120 TRANSLATION_FACTORS 43 0.54307544 0.774744 1 G121 BLOOD_CLOTTING_CASCADE 19 0.4796201 0.7759401 1 G122 HSA00563_GLYCOSYLPHOSPHATIDYLINOSIT18 0.5363871 0.7777266 1 G123 HSA04350_TGF_BETA_SIGNALING_PATHW81 0.46278316 0.7796834 1 G124 HSA00790_FOLATE_BIOSYNTHESIS 35 0.47172058 0.7807829 1 G125 HSA00565_ETHER_LIPID_METABOLISM 27 0.5098232 0.783599 1 G126 TH1TH2PATHWAY 17 0.57599527 0.78363454 1 G127 FRUCTOSE_AND_MANNOSE_METABOLISM24 0.48223248 0.7845406 1 G128 NKTPATHWAY 25 0.49105725 0.78531396 1 G129 HSA00052_GALACTOSE_METABOLISM 27 0.47261858 0.7860272 1 G130 LYSINE_DEGRADATION 28 0.5123967 0.7899286 1 G131 HSA04662_B_CELL_RECEPTOR_SIGNALING 59 0.44188768 0.79023176 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 1:09 PM
G132 HSA05223_NON_SMALL_CELL_LUNG_CAN 52 0.64483774 0.7931399 1 G133 HSA00030_PENTOSE_PHOSPHATE_PATHW25 0.61755955 0.8063857 1 G134 CARM_ERPATHWAY 26 0.6391501 0.83197266 1 G135 HSA00590_ARACHIDONIC_ACID_METABOLI48 0.7292447 0.87807375 1 G136 INFLAMPATHWAY 29 0.70688605 0.9041992 1 G137 HSA00512_O_GLYCAN_BIOSYNTHESIS 20 0.7014068 0.90501267 1 G138 HSA04640_HEMATOPOIETIC_CELL_LINEAGE80 0.8226563 0.95208323 1 G139 ALKPATHWAY 32 0.81517774 0.9579018 1 G140 ST_INTERLEUKIN_4_PATHWAY 26 0.82819813 0.9942327 1 G141 RARRXRPATHWAY 15 0.7861767 1 1 G142 TOB1PATHWAY 16 0.8270796 1 1 G143 HSA00071_FATTY_ACID_METABOLISM 39 0.8320683 1 1 G144 STEMPATHWAY 15 0.8439509 1 1 G145 IL7PATHWAY 16 0.8519807 1 1 G146 HSA00120_BILE_ACID_BIOSYNTHESIS 31 0.8594532 1 1 G147 HSA00624_1_AND_2_METHYLNAPHTHALE 16 0.8630002 1 1 G148 HSA03022_BASAL_TRANSCRIPTION_FACTO28 0.86477154 1 1 G149 ARFPATHWAY 15 0.8727442 1 1 G150 OVARIAN_INFERTILITY_GENES 23 0.8812885 1 1 G151 RNA_TRANSCRIPTION_REACTOME 33 0.88706565 1 1 G152 HSA00903_LIMONENE_AND_PINENE_DEGR24 0.9189605 1 1 G153 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES34 0.9215457 1 1 G154 GLYCOSPHINGOLIPID_METABOLISM 21 0.92227674 1 1 G155 HSA00632_BENZOATE_DEGRADATION_VIA23 0.92399377 1 1 G156 SMALL_LIGAND_GPCRS 17 0.9359918 1 1 G157 HSA00220_UREA_CYCLE_AND_METABOLIS27 0.9437204 1 1 G158 HSA00480_GLUTATHIONE_METABOLISM 32 0.9483773 1 1 G159 CYTOKINEPATHWAY 20 0.95312804 1 1 G160 HSA04614_RENIN_ANGIOTENSIN_SYSTEM 15 0.9551223 1 1 G161 GLUTATHIONE_METABOLISM 27 0.95837384 1 1 G162 DCPATHWAY 20 0.9701237 1 1 G163 HSA00361_GAMMA_HEXACHLOROCYCLOH19 0.9750246 1 1 G164 GLYCINE_SERINE_AND_THREONINE_META 30 0.98330617 1 1 G165 HSA00260_GLYCINE_SERINE_AND_THREON36 0.9919306 1 1 G166 AMINOACYL_TRNA_BIOSYNTHESIS 20 1 1 1 G167 HSA00271_METHIONINE_METABOLISM 16 1 1 1 G168 HSA00970_AMINOACYL_TRNA_BIOSYNTHE26 1 1 1 G169 HSA03010_RIBOSOME 55 1 1 1 G170 HSA03020_RNA_POLYMERASE 18 1 1 1 G171 HSA03050_PROTEASOME 22 1 1 1 G172 HSA04950_MATURITY_ONSET_DIABETES_O18 1 1 1 G173 PROTEASOMEPATHWAY 21 1 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S8 ClickTable.htm here to download Table: Table S8.pdf 2/24/11 1:11 PM
Table S8. Canonical pathways associated with normal samples in GSEAndes (Glioblastoma) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 TYPE_III_SECRETION_SYSTEM 18 0.006151143 0.2926041 0.4147 G2 PHOTOSYNTHESIS 19 0.005690162 0.32111675 0.5345 G3 CARBON_FIXATION 19 0.0974359 0.38776284 0.9855 G4 PGC1APATHWAY 23 0.001983253 0.38932317 0.8318 G5 PYK2PATHWAY 27 0.031078225 0.40010878 0.9806 G6 ETSPATHWAY 15 0.06946084 0.40587983 0.9853 G7 GPCRPATHWAY 33 0.028091082 0.41271752 0.9902 G8 HSA04742_TASTE_TRANSDUCTION 34 0.01295667 0.42143232 0.9799 G9 HSA05120_EPITHELIAL_CELL_SIGNALING_I61 4.07E-04 0.4254495 0.9755 G10 AT1RPATHWAY 34 0.030348364 0.42909533 0.9961 G11 FMLPPATHWAY 34 0.002552106 0.4300764 0.9648 G12 NOS1PATHWAY 21 0.005888768 0.4310761 0.8227 G13 HSA05110_CHOLERA_INFECTION 36 0.00962523 0.43531546 0.9719 G14 CHREBPPATHWAY 16 0.20289564 0.43862557 0.9987 G15 FLAGELLAR_ASSEMBLY 18 0.006151143 0.43890613 0.4147 G16 MONOAMINE_GPCRS 28 0.048401035 0.43923357 0.9938 G17 HSA05030_AMYOTROPHIC_LATERAL_SCLE 17 0.06709068 0.43965596 0.9951 G18 CCR3PATHWAY 22 0.12883691 0.44028074 0.998 G19 HSA04720_LONG_TERM_POTENTIATION 66 0.016274864 0.44192788 0.9959 G20 OXIDATIVE_PHOSPHORYLATION 54 0.11068234 0.44254205 0.7208 G21 CALCINEURINPATHWAY 18 0.005971993 0.44392386 0.8983 G22 GLUTAMATE_METABOLISM 22 0.062154107 0.44410375 0.9993 G23 HSA04916_MELANOGENESIS 90 0.017712334 0.44849843 1 G24 BIOPEPTIDESPATHWAY 38 0.05612356 0.45119524 0.9993 G25 PAR1PATHWAY 19 0.03581902 0.45126432 0.9987 G26 HSA04740_OLFACTORY_TRANSDUCTION 28 0.038428325 0.45188004 0.9979 G27 NDKDYNAMINPATHWAY 17 0.04389313 0.45266932 0.962 G28 INSULINPATHWAY 21 0.1349857 0.45269537 0.9999 G29 CITRATE_CYCLE_TCA_CYCLE 19 0.11920415 0.45284486 0.7864 G30 HSA04540_GAP_JUNCTION 85 0.027165443 0.45419165 1 G31 TCRPATHWAY 42 0.10716498 0.45481762 1 G32 ST_WNT_CA2_CYCLIC_GMP_PATHWAY 19 0.08426244 0.45493028 0.9999 G33 HSA04012_ERBB_SIGNALING_PATHWAY 84 0.02245287 0.45502096 1 G34 HSA00251_GLUTAMATE_METABOLISM 27 0.074610956 0.45657626 0.9999 G35 WNTPATHWAY 25 0.0772384 0.45714924 0.9992 G36 PHOSPHATIDYLINOSITOL_SIGNALING_SYST85 0.00791952 0.45742455 0.9993 G37 HSA01510_NEURODEGENERATIVE_DISEAS 35 0.02106383 0.45767817 0.9976 G38 HSA04130_SNARE_INTERACTIONS_IN_VESI30 0.101626836 0.4602815 0.9999 G39 HSA04320_DORSO_VENTRAL_AXIS_FORM 23 0.11760154 0.4609012 0.9999 G40 TPOPATHWAY 23 0.13228655 0.4612297 1 G41 ACTINYPATHWAY 16 0.2614601 0.46179014 0.9986 G42 CREBPATHWAY 26 0.13598418 0.46207938 1 G43 KERATINOCYTEPATHWAY 43 0.027546572 0.46279415 0.9999 G44 HSA04730_LONG_TERM_DEPRESSION 73 0.014457296 0.46307737 0.9994 G45 EPOPATHWAY 19 0.21403712 0.4639487 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 1:11 PM
G46 HSA00020_CITRATE_CYCLE 23 0.16563189 0.4642886 0.999 G47 MEF2DPATHWAY 17 0.020137014 0.46480647 0.942 G48 SIG_REGULATION_OF_THE_ACTIN_CYTOSK33 0.10135135 0.46495572 0.9999 G49 SIG_CD40PATHWAYMAP 33 0.07622274 0.46506202 0.9999 G50 ST_INTEGRIN_SIGNALING_PATHWAY 75 0.03729366 0.46599495 1 G51 CXCR4PATHWAY 23 0.1535133 0.46791947 1 G52 PEPTIDE_GPCRS 68 0.027314723 0.46797317 0.9992 G53 HSA04140_REGULATION_OF_AUTOPHAGY28 0.2376978 0.46852413 0.9561 G54 IGF1PATHWAY 20 0.12237281 0.46882796 0.9999 G55 FCER1PATHWAY 37 0.039054472 0.47046107 0.9999 G56 HSA04912_GNRH_SIGNALING_PATHWAY 92 0.036590617 0.47120798 1 G57 HDACPATHWAY 29 0.15958844 0.47122002 1 G58 CDMACPATHWAY 16 0.052070767 0.4714464 0.9976 G59 ERK5PATHWAY 17 0.15643448 0.47462806 0.9999 G60 NGFPATHWAY 19 0.20899315 0.47515908 1 G61 HSA00190_OXIDATIVE_PHOSPHORYLATIO 98 0.32461712 0.47580388 0.9999 G62 MAPKPATHWAY 84 0.0125 0.47643948 0.9997 G63 BCRPATHWAY 34 0.07065893 0.47659066 0.9998 G64 G_PROTEIN_SIGNALING 85 0.06603357 0.48019096 1 G65 GPCRDB_OTHER 47 0.04980121 0.4836502 1 G66 METPATHWAY 33 0.13297555 0.48559433 1 G67 ST_GRANULE_CELL_SURVIVAL_PATHWAY 27 0.17081329 0.4857975 1 G68 HSA04660_T_CELL_RECEPTOR_SIGNALING 90 0.113395505 0.48733276 1 G69 HSA00410_BETA_ALANINE_METABOLISM 24 0.0833161 0.4880606 0.9997 G70 ST_GA12_PATHWAY 21 0.19363675 0.48853287 1 G71 WNT_SIGNALING 58 0.09090909 0.4891467 1 G72 VIPPATHWAY 25 0.15404364 0.4892523 1 G73 HSA00710_CARBON_FIXATION 21 0.2827456 0.49123365 1 G74 RAC1PATHWAY 22 0.14782783 0.49261665 1 G75 EGFPATHWAY 27 0.17114094 0.4927761 1 G76 ST_DIFFERENTIATION_PATHWAY_IN_PC1243 0.15062676 0.49338454 1 G77 NFATPATHWAY 50 0.11765999 0.4964161 1 G78 CK1PATHWAY 15 0.035054173 0.49678352 0.9377 G79 HSA04070_PHOSPHATIDYLINOSITOL_SIGN 67 0.105367355 0.49754727 1 G80 ST_T_CELL_SIGNAL_TRANSDUCTION 42 0.11765981 0.49795538 1 G81 NO1PATHWAY 27 0.17473178 0.5003302 1 G82 IL2PATHWAY 22 0.26372015 0.50161403 1 G83 GLEEVECPATHWAY 22 0.18704204 0.5042332 1 G84 ST_G_ALPHA_I_PATHWAY 34 0.098473445 0.50922436 1 G85 HSA00562_INOSITOL_PHOSPHATE_METAB40 0.12606113 0.51298124 1 G86 HSA04930_TYPE_II_DIABETES_MELLITUS 40 0.14792278 0.5157257 1 G87 ERKPATHWAY 30 0.19965577 0.5166907 1 G88 IGF1RPATHWAY 15 0.2884351 0.52646923 1 G89 ALANINE_AND_ASPARTATE_METABOLISM 18 0.26564145 0.53112394 1 G90 SIG_CHEMOTAXIS 42 0.18495892 0.5354275 1 G91 GPCRDB_CLASS_B_SECRETIN_LIKE 22 0.2279544 0.5384931 1 G92 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_30 0.22180134 0.5427035 1 G93 MPRPATHWAY 22 0.2559322 0.5432541 1 G94 PTENPATHWAY 16 0.36559352 0.5547663 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 1:11 PM
G95 PTDINSPATHWAY 20 0.33111784 0.5562431 1 G96 PDGFPATHWAY 27 0.2585483 0.57617223 1 G97 P38MAPKPATHWAY 39 0.24316663 0.5816637 1 G98 HSA00252_ALANINE_AND_ASPARTATE_M 28 0.29138225 0.5823276 1 G99 HSA04370_VEGF_SIGNALING_PATHWAY 66 0.22374617 0.60907185 1 G100 HSA01031_GLYCAN_STRUCTURES_BIOSYN 53 0.24379991 0.6148761 1 G101 NKCELLSPATHWAY 17 0.35365105 0.62024987 1 G102 ST_MYOCYTE_AD_PATHWAY 24 0.29390094 0.62069064 1 G103 HSA04520_ADHERENS_JUNCTION 72 0.2760598 0.6388838 1 G104 HSA04150_MTOR_SIGNALING_PATHWAY 44 0.32172537 0.64330584 1 G105 INOSITOL_PHOSPHATE_METABOLISM 22 0.33952528 0.64364254 1 G106 EIF4PATHWAY 24 0.3707108 0.64660233 1 G107 SIG_PIP3_SIGNALING_IN_CARDIAC_MYOC 64 0.28673685 0.66392624 1 G108 HSA00602_GLYCOSPHINGOLIPID_BIOSYNT 20 0.43117487 0.6852777 1 G109 HSA04920_ADIPOCYTOKINE_SIGNALING_P68 0.3323293 0.6858319 1 G110 HSA04664_FC_EPSILON_RI_SIGNALING_PA73 0.3457035 0.6862563 1 G111 CCR5PATHWAY 17 0.41707265 0.69352895 1 G112 BETA_ALANINE_METABOLISM 25 0.40375 0.69511086 1 G113 HSA05211_RENAL_CELL_CARCINOMA 67 0.359516 0.6952819 1 G114 SA_B_CELL_RECEPTOR_COMPLEXES 24 0.40293702 0.69726205 1 G115 SA_PTEN_PATHWAY 17 0.4417305 0.7009173 1 G116 ST_JNK_MAPK_PATHWAY 40 0.4094667 0.7143743 1 G117 HSA00150_ANDROGEN_AND_ESTROGEN_ 40 0.43852702 0.71936506 1 G118 NITROGEN_METABOLISM 20 0.45052633 0.7336031 1 G119 ST_ADRENERGIC 33 0.4599317 0.75263 1 G120 PENTOSE_PHOSPHATE_PATHWAY 22 0.5037097 0.7847531 1 G121 GCRPATHWAY 17 0.53334767 0.7868063 1 G122 CIRCADIAN_EXERCISE 39 0.49728426 0.7868709 1 G123 HSA05214_GLIOMA 62 0.49281698 0.78837895 1 G124 BADPATHWAY 21 0.51655906 0.79263675 1 G125 KREBS_TCA_CYCLE 26 0.54339623 0.7986949 1 G126 PPARAPATHWAY 51 0.57094806 0.8118809 1 G127 BUTANOATE_METABOLISM 26 0.5628368 0.81269926 1 G128 HSA00534_HEPARAN_SULFATE_BIOSYNTH16 0.5750732 0.8142671 1 G129 SA_TRKA_RECEPTOR 16 0.5589112 0.8161697 1 G130 HSA00910_NITROGEN_METABOLISM 23 0.5633833 0.8162778 1 G131 HSA00564_GLYCEROPHOSPHOLIPID_META55 0.5563832 0.81854606 1 G132 SIG_BCR_SIGNALING_PATHWAY 44 0.5262414 0.82068527 1 G133 CALCINEURIN_NF_AT_SIGNALING 90 0.61554027 0.82333606 1 G134 GHPATHWAY 27 0.5912469 0.8284568 1 G135 GLYCEROPHOSPHOLIPID_METABOLISM 45 0.60534495 0.82925045 1 G136 ST_B_CELL_ANTIGEN_RECEPTOR 39 0.5767876 0.8329674 1 G137 HSA00650_BUTANOATE_METABOLISM 40 0.6194171 0.86160356 1 G138 HSA00330_ARGININE_AND_PROLINE_MET29 0.63581973 0.8656789 1 G139 CHOLESTEROL_BIOSYNTHESIS 15 0.64423805 0.87000495 1 G140 HSA05218_MELANOMA 68 0.71321 0.8734348 1 G141 ATP_SYNTHESIS 18 0.006151143 0.87781227 0.4147 G142 ST_WNT_BETA_CATENIN_PATHWAY 28 0.67820305 0.8907194 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 1:11 PM
G143 STRIATED_MUSCLE_CONTRACTION 33 0.65108913 0.89191145 1 G144 HSA03320_PPAR_SIGNALING_PATHWAY 59 0.7620142 0.9168451 1 G145 ST_GAQ_PATHWAY 27 0.746748 0.9275856 1 G146 EDG1PATHWAY 25 0.76011807 0.9302059 1 G147 RHOPATHWAY 29 0.7078051 0.93138266 1 G148 ANDROGEN_AND_ESTROGEN_METABOLIS 22 0.6869648 0.9349491 1 G149 HSA00100_BIOSYNTHESIS_OF_STEROIDS 23 0.68446296 0.93546075 1 G150 GLYCEROLIPID_METABOLISM 39 0.78626114 0.9450752 1 G151 PYRUVATE_METABOLISM 34 0.7235181 0.9475109 1 G152 HSA00340_HISTIDINE_METABOLISM 33 0.7888036 0.9701138 1 G153 HSA00350_TYROSINE_METABOLISM 48 0.82808566 0.97166246 1 G154 UREA_CYCLE_AND_METABOLISM_OF_AMI16 0.7816462 0.974084 1 G155 ST_PHOSPHOINOSITIDE_3_KINASE_PATHW33 0.84736526 0.9744538 1 G156 GLYCOLYSIS_AND_GLUCONEOGENESIS 42 0.78450704 0.97998303 1 G157 HISTIDINE_METABOLISM 23 0.82219034 0.9804446 1 G158 SIG_INSULIN_RECEPTOR_PATHWAY_IN_CA50 0.8461234 0.98197037 1 G159 ST_GA13_PATHWAY 35 0.84741974 0.98397547 1 G160 SIG_IL4RECEPTOR_IN_B_LYPHOCYTES 27 0.85180056 0.9857705 1 G161 HSA00561_GLYCEROLIPID_METABOLISM 48 0.8766194 0.98876125 1 G162 HSA00960_ALKALOID_BIOSYNTHESIS_II 15 0.8850938 0.99066657 1 G163 PROPANOATE_METABOLISM 29 0.9426178 0.99152744 1 G164 HSA00980_METABOLISM_OF_XENOBIOTIC50 0.9717314 0.99341846 1 G165 HSA00360_PHENYLALANINE_METABOLISM26 0.9817511 0.99433476 1 G166 HSA00620_PYRUVATE_METABOLISM 36 0.9270678 0.99450064 1 G167 TYROSINE_METABOLISM 27 0.9844656 0.9958936 1 G168 VALINE_LEUCINE_AND_ISOLEUCINE_DEGR34 0.9758182 0.9968055 1 G169 TRYPTOPHAN_METABOLISM 51 0.9958584 0.9988909 1 G170 HSA00600_SPHINGOLIPID_METABOLISM 29 0.9446388 0.9997487 1 G171 PHENYLALANINE_METABOLISM 20 0.8844435 0.9998803 1 G172 NO2IL12PATHWAY 15 0.81486225 1 1 G173 HSA00640_PROPANOATE_METABOLISM 29 0.8808598 1 1 G174 BILE_ACID_BIOSYNTHESIS 23 0.8923267 1 1 G175 NUCLEAR_RECEPTORS 38 0.8925956 1 1 G176 GAMMA_HEXACHLOROCYCLOHEXANE_DE 26 0.89452577 1 1 G177 IL12PATHWAY 19 0.89785284 1 1 G178 HSA00280_VALINE_LEUCINE_AND_ISOLEU42 0.90640295 1 1 G179 ARGININE_AND_PROLINE_METABOLISM 40 0.93050987 1 1 G180 GLUCONEOGENESIS 48 0.93142855 1 1 G181 GLYCOLYSIS 48 0.93142855 1 1 G182 HSA00010_GLYCOLYSIS_AND_GLUCONEOG55 0.93699354 1 1 G183 HSA04340_HEDGEHOG_SIGNALING_PATH 45 0.9413307 1 1 G184 HSA00380_TRYPTOPHAN_METABOLISM 49 0.9717608 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S9a ClickTable.htm here to download Table: Table S9a.pdf 2/24/11 2:29 PM
Table S9a. Canonical pathways associated with case samples in GSAAzs-ks (CD) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 PROTEASOME 15 0.045489237 0.046908155 0.0361 G2 ST_G_ALPHA_I_PATHWAY 33 0.000186567 0.04998536 0.1234 G3 AMINOACYL_TRNA_BIOSYNTHESIS 17 0.001757778 0.0528578 0.1006 G4 HSA00970_AMINOACYL_TRNA_BIOSYNTHESIS 19 0.007593148 0.057286218 0.2298 G5 HSA04940_TYPE_I_DIABETES_MELLITUS 36 0.000192271 0.058629896 0.1749 G6 SIG_BCR_SIGNALING_PATHWAY 43 0.000191681 0.0657223 0.2262 G7 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_CHEMOTAXIS_PATHWAY 29 0 0.06821794 0.0876 G8 SA_B_CELL_RECEPTOR_COMPLEXES 23 0.001487265 0.11424339 0.4672 G9 PROTEASOMEPATHWAY 21 0.07235745 0.114782855 0.4286 G10 TPOPATHWAY 23 0.004609995 0.19574456 0.7077 G11 HSA00565_ETHER_LIPID_METABOLISM 19 0.01147159 0.19970295 0.6858 G12 HSA04514_CELL_ADHESION_MOLECULES 97 0 0.23449484 0.7891 G13 LAIRPATHWAY 15 0.06199508 0.3002796 0.871 G14 HSA03050_PROTEASOME 22 0.16595675 0.3166331 0.9119 G15 HSA04612_ANTIGEN_PROCESSING_AND_PRESENTATION 57 0.022718294 0.32600832 0.9049 G16 EICOSANOID_SYNTHESIS 15 0.050516024 0.3437762 0.9493 G17 HSA05219_BLADDER_CANCER 41 0.005116096 0.3455003 0.9564 G18 N_GLYCAN_BIOSYNTHESIS 17 0.042595614 0.3573951 0.9471 G19 NO2IL12PATHWAY 15 0.05214286 0.35919517 0.941 G20 HSA04512_ECM_RECEPTOR_INTERACTION 73 0.004308656 0.35986346 0.9657 G21 HSA01510_NEURODEGENERATIVE_DISEASES 35 0.011143131 0.3700532 0.9764 G22 IL6PATHWAY 21 0.03524804 0.38353136 0.9754 G23 HSA05050_DENTATORUBROPALLIDOLUYSIAN_ATROPHY 15 0.12004175 0.4571691 0.9923 G24 TH1TH2PATHWAY 16 0.0801973 0.46074048 0.9914 G25 SA_MMP_CYTOKINE_CONNECTION 15 0.157007 0.4655976 0.9944 G26 IL7PATHWAY 16 0.10406361 0.47166854 0.9937 G27 HSA04920_ADIPOCYTOKINE_SIGNALING_PATHWAY 62 0.011043742 0.4828477 0.996 G28 PROSTAGLANDIN_SYNTHESIS_REGULATION 24 0.06612996 0.57705176 0.9986 G29 ST_T_CELL_SIGNAL_TRANSDUCTION 39 0.05446792 0.5879191 0.999 G30 WNT_SIGNALING 49 0.2864685 0.6162755 1 G31 HSA04370_VEGF_SIGNALING_PATHWAY 58 0.25762782 0.6189597 1 G32 ST_TUMOR_NECROSIS_FACTOR_PATHWAY 27 0.3328347 0.62159973 1 G33 HSA00530_AMINOSUGARS_METABOLISM 17 0.40592647 0.6220254 1 G34 APOPTOSIS 63 0.22641128 0.62237215 1 G35 CDMACPATHWAY 15 0.43046588 0.6226814 1 G36 HSA00252_ALANINE_AND_ASPARTATE_METABOLISM 23 0.4222831 0.6230483 1 G37 HSA01430_CELL_COMMUNICATION 93 0.18261759 0.6259194 1 G38 GALACTOSE_METABOLISM 21 0.33452782 0.62653214 1 G39 ETSPATHWAY 16 0.43917018 0.6270921 1 G40 HIVNEFPATHWAY 51 0.2124772 0.62740386 1 G41 ST_P38_MAPK_PATHWAY 32 0.32675523 0.6276679 1 G42 HSA00330_ARGININE_AND_PROLINE_METABOLISM 26 0.4171326 0.6282504 1 G43 HSA01030_GLYCAN_STRUCTURES_BIOSYNTHESIS_1 52 0.175502 0.62868977 1 G44 HSA00380_TRYPTOPHAN_METABOLISM 42 0.27741313 0.62911904 1 G45 PURINE_METABOLISM 97 0.21485826 0.62965226 1 G46 CHEMICALPATHWAY 20 0.3624422 0.63013244 1 G47 HSA05212_PANCREATIC_CANCER 70 0.22978126 0.63085455 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 2:29 PM
G48 HSA05110_CHOLERA_INFECTION 33 0.36679536 0.63160896 1 G49 FRUCTOSE_AND_MANNOSE_METABOLISM 21 0.39586553 0.63173026 1 G50 HSA05215_PROSTATE_CANCER 80 0.2805843 0.6319566 1 G51 EIF4PATHWAY 23 0.38281107 0.6319655 1 G52 STEMPATHWAY 15 0.42919657 0.6321051 1 G53 41BBPATHWAY 18 0.36330476 0.6328554 1 G54 IGF1RPATHWAY 15 0.46788663 0.6335055 1 G55 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS 41 0.35191363 0.63431996 1 G56 PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 83 0.22989924 0.63494253 1 G57 INTEGRINPATHWAY 33 0.29723293 0.6353673 1 G58 STRESSPATHWAY 24 0.36287627 0.6357702 1 G59 GCRPATHWAY 16 0.24763292 0.63615537 1 G60 BREAST_CANCER_ESTROGEN_SIGNALING 89 0.04769737 0.63777936 1 G61 FMLPPATHWAY 33 0.28065294 0.64041376 1 G62 CARBON_FIXATION 18 0.3835566 0.640466 1 G63 IL12PATHWAY 20 0.33409178 0.64059997 1 G64 ARAPPATHWAY 17 0.18292683 0.64078075 1 G65 ST_ERK1_ERK2_MAPK_PATHWAY 25 0.36026442 0.64228475 1 G66 INOSITOL_PHOSPHATE_METABOLISM 22 0.43244246 0.6431726 1 G67 CCR3PATHWAY 22 0.29032856 0.64325935 1 G68 RACCYCDPATHWAY 22 0.20633188 0.6444244 1 G69 HSA00510_N_GLYCAN_BIOSYNTHESIS 24 0.18920916 0.6448085 1 G70 VEGFPATHWAY 26 0.28823864 0.6449257 1 G71 CALCINEURIN_NF_AT_SIGNALING 89 0.30976915 0.6458093 1 G72 ST_B_CELL_ANTIGEN_RECEPTOR 38 0.1018537 0.645983 1 G73 ST_GA13_PATHWAY 35 0.36859667 0.6468687 1 G74 UCALPAINPATHWAY 16 0.3204758 0.6468829 1 G75 INTRINSICPATHWAY 22 0.17392896 0.6470459 0.9999 G76 PDGFPATHWAY 27 0.15013252 0.6483424 1 G77 CSKPATHWAY 21 0.3289012 0.64915574 1 G78 CCR5PATHWAY 16 0.18678571 0.6495678 0.9999 G79 CELLCYCLEPATHWAY 23 0.2406761 0.64986646 1 G80 HSA04664_FC_EPSILON_RI_SIGNALING_PATHWAY 64 0.05310621 0.6499527 1 G81 G1PATHWAY 25 0.28136954 0.6500412 1 G82 IL2RBPATHWAY 34 0.38726738 0.6502139 1 G83 APOPTOSIS_KEGG 46 0.07605178 0.65362424 0.9999 G84 HSA04610_COMPLEMENT_AND_COAGULATION_CASCADES 61 0.03870458 0.65544355 0.9998 G85 HSA05222_SMALL_CELL_LUNG_CANCER 83 0.05388855 0.6563615 1 G86 AMIPATHWAY 21 0.3289012 0.6568838 1 G87 NTHIPATHWAY 21 0.20983545 0.65735453 0.9999 G88 TOLLPATHWAY 27 0.15199542 0.6574628 1 G89 HSA00052_GALACTOSE_METABOLISM 24 0.30682763 0.6590696 1 G90 NKTPATHWAY 26 0.15190604 0.65992975 0.9999 G91 PPARAPATHWAY 49 0.0739157 0.66027886 0.9999 G92 TNFR2PATHWAY 18 0.19867203 0.66082114 0.9998 G93 EDG1PATHWAY 24 0.1980722 0.6608223 1 G94 TELPATHWAY 15 0.19625 0.6609031 0.9997 G95 HSA04670_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION 89 0.32355934 0.66301227 1 G96 INFLAMPATHWAY 28 0.15036301 0.6641058 0.9999 G97 HSA05040_HUNTINGTONS_DISEASE 24 0.10915695 0.66537994 0.9996 G98 IL1RPATHWAY 28 0.18601532 0.66563743 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 2:29 PM
G99 CYTOKINEPATHWAY 20 0.12923135 0.6661111 0.9995 G100 HSA00051_FRUCTOSE_AND_MANNOSE_METABOLISM 29 0.08912793 0.6662633 0.9997 G101 ERYTHPATHWAY 15 0.38386697 0.6663126 1 G102 CK1PATHWAY 16 0.3696894 0.6666994 1 G103 CASPASEPATHWAY 21 0.3398917 0.66791975 1 G104 HSA04660_T_CELL_RECEPTOR_SIGNALING_PATHWAY 84 0.07368207 0.668165 1 G105 CARM_ERPATHWAY 24 0.22645618 0.66834307 1 G106 PROSTAGLANDIN_AND_LEUKOTRIENE_METABOLISM 26 0.07741677 0.66836023 0.9997 G107 MITOCHONDRIAPATHWAY 18 0.35411334 0.66936946 1 G108 KERATINOCYTEPATHWAY 42 0.19413629 0.67132664 1 G109 HSA03030_DNA_POLYMERASE 16 0.19207746 0.6720195 0.9999 G110 MAPKPATHWAY 79 0.35691512 0.67374086 1 G111 ST_INTEGRIN_SIGNALING_PATHWAY 72 0.4340571 0.6741445 1 G112 CIRCADIAN_EXERCISE 39 0.4434935 0.6747078 1 G113 DEATHPATHWAY 31 0.21465044 0.6749307 1 G114 HSA00240_PYRIMIDINE_METABOLISM 57 0.36851346 0.67503655 1 G115 GPCRDB_OTHER 34 0.47547683 0.67508686 1 G116 AKTPATHWAY 17 0.36006343 0.67629546 1 G117 EPOPATHWAY 19 0.4866727 0.6766457 1 G118 RELAPATHWAY 16 0.31763285 0.67665625 1 G119 FASPATHWAY 26 0.28182158 0.677164 1 G120 HSA05010_ALZHEIMERS_DISEASE 19 0.31573218 0.67760366 1 G121 DNA_REPLICATION_REACTOME 39 0.46087804 0.67762345 1 G122 HSA04130_SNARE_INTERACTIONS_IN_VESICULAR_TRANSPORT 26 0.49097002 0.6778709 1 G123 HSA04330_NOTCH_SIGNALING_PATHWAY 32 0.48108724 0.6784504 1 G124 IL3PATHWAY 15 0.19063888 0.67885464 0.9999 G125 INTEGRIN_MEDIATED_CELL_ADHESION_KEGG 78 0.16613482 0.6790655 1 G126 VIPPATHWAY 25 0.49518093 0.6802379 1 G127 P53PATHWAY 15 0.5344086 0.68029475 1 G128 UBIQUITIN_MEDIATED_PROTEOLYSIS 20 0.32270136 0.681682 1 G129 PYRIMIDINE_METABOLISM 45 0.4103355 0.6817913 1 G130 INSULINPATHWAY 21 0.5253928 0.6835768 1 G131 GSK3PATHWAY 23 0.31519598 0.684607 1 G132 HSA05221_ACUTE_MYELOID_LEUKEMIA 50 0.40158698 0.68522274 1 G133 WNTPATHWAY 23 0.2986828 0.6895146 1 G134 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY 87 0.13485901 0.69084585 1 G135 SPPAPATHWAY 21 0.3097265 0.69248056 1 G136 HSA04640_HEMATOPOIETIC_CELL_LINEAGE 82 0.054604728 0.6954564 0.9999 G137 TIDPATHWAY 17 0.32014638 0.6992223 1 G138 ST_INTERLEUKIN_4_PATHWAY 24 0.25405708 0.7012456 1 G139 CXCR4PATHWAY 23 0.5487132 0.7043719 1 G140 NFKBPATHWAY 22 0.28623787 0.7062801 1 G141 HSA05220_CHRONIC_MYELOID_LEUKEMIA 71 0.4848178 0.7121053 1 G142 IGF1PATHWAY 20 0.31260288 0.7147861 1 G143 HSA04210_APOPTOSIS 75 0.5172902 0.7163722 1 G144 HSA05120_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_I56 0.52124476 0.7164027 1 G145 TNFR1PATHWAY 27 0.5420669 0.71795297 1 G146 CELL_CYCLE_KEGG 76 0.5064883 0.7185705 1 G147 HSA00590_ARACHIDONIC_ACID_METABOLISM 37 0.5428256 0.72071534 1 G148 APOPTOSIS_GENMAPP 41 0.51897454 0.7223726 1 G149 SIG_IL4RECEPTOR_IN_B_LYPHOCYTES 26 0.5519518 0.7233537 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 2:29 PM
G150 BLOOD_CLOTTING_CASCADE 19 0.5908756 0.7312183 1 G151 GHPATHWAY 27 0.61430734 0.7641795 1 G152 ACTINYPATHWAY 16 0.61362433 0.7791796 1 G153 CHOLESTEROL_BIOSYNTHESIS 15 0.56582445 0.78394496 1 G154 HSA00710_CARBON_FIXATION 19 0.6701308 0.8045871 1 G155 ST_FAS_SIGNALING_PATHWAY 52 0.68064386 0.8063733 1 G156 HSA04110_CELL_CYCLE 98 0.65633076 0.8075493 1 G157 P38MAPKPATHWAY 39 0.66227895 0.8078213 1 G158 HSA00790_FOLATE_BIOSYNTHESIS 27 0.68999815 0.8078941 1 G159 G2PATHWAY 22 0.6923077 0.80879337 1 G160 G1_TO_S_CELL_CYCLE_REACTOME 62 0.68782437 0.81054616 1 G161 FCER1PATHWAY 36 0.71568626 0.82425886 1 G162 HSA05131_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EPEC 33 0.7113619 0.8259873 1 G163 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS 27 0.7103733 0.8291729 1 G164 HSA05130_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EHEC 33 0.7113619 0.8310547 1 G165 HSA01032_GLYCAN_STRUCTURES_DEGRADATION 21 0.7303391 0.8420828 1 G166 ARGININE_AND_PROLINE_METABOLISM 38 0.7417623 0.8421482 1 G167 TRYPTOPHAN_METABOLISM 47 0.7096135 0.8433561 1 G168 HSA04115_P53_SIGNALING_PATHWAY 52 0.78531414 0.84605753 1 G169 RNA_TRANSCRIPTION_REACTOME 29 0.7331502 0.8606844 1 G170 MRNA_PROCESSING_REACTOME 96 0.8024209 0.87485206 1 G171 PENTOSE_PHOSPHATE_PATHWAY 19 0.7420328 0.8764394 1 G172 ATMPATHWAY 17 0.7843316 0.8893402 1 G173 HSA00030_PENTOSE_PHOSPHATE_PATHWAY 21 0.7893387 0.90539026 1 G174 HSA00100_BIOSYNTHESIS_OF_STEROIDS 21 0.737931 0.9127142 1 G175 ATP_SYNTHESIS 17 1 1 1 G176 ATRBRCAPATHWAY 17 1 1 1 G177 FLAGELLAR_ASSEMBLY 17 1 1 1 G178 GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 23 1 1 1 G179 HSA00190_OXIDATIVE_PHOSPHORYLATION 84 1 1 1 G180 HSA00340_HISTIDINE_METABOLISM 27 1 1 1 G181 HSA01031_GLYCAN_STRUCTURES_BIOSYNTHESIS_2 40 1 1 1 G182 HSA03010_RIBOSOME 54 1 1 1 G183 HSA03022_BASAL_TRANSCRIPTION_FACTORS 25 1 1 1 G184 HSA04140_REGULATION_OF_AUTOPHAGY 23 1 1 1 G185 HSP27PATHWAY 15 1 1 1 G186 HYPERTROPHY_MODEL 17 1 1 1 G187 MONOAMINE_GPCRS 22 1 1 1 G188 NDKDYNAMINPATHWAY 15 1 1 1 G189 OXIDATIVE_PHOSPHORYLATION 47 1 1 1 G190 PHOTOSYNTHESIS 18 1 1 1 G191 RIBOSOMAL_PROTEINS 77 1 1 1 G192 SA_PTEN_PATHWAY 16 1 1 1 G193 SA_TRKA_RECEPTOR 16 1 1 1 G194 ST_WNT_BETA_CATENIN_PATHWAY 23 1 1 1 G195 TRANSLATION_FACTORS 39 1 1 1 G196 TYPE_III_SECRETION_SYSTEM 17 1 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S9b ClickTable.htm here to download Table: Table S9b.pdf 2/24/11 2:32 PM
Table S9b. Canonical pathways associated with case samples in GSAAzs-ks (CD) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 KEGG_PROTEASOME http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PROTEASOME.html G2 ST_G_ALPHA_I_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_G_ALPHA_I_PATHWAY.html G3 KEGG_AMINOACYL_TRNA_BIOSYNTHESIS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_AMINOACYL_TRNA_BIOSYNTHESIS.html G4 KEGG_AMINOACYL_TRNA_BIOSYNTHESIS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_AMINOACYL_TRNA_BIOSYNTHESIS.html G5 KEGG_TYPE_I_DIABETES_MELLITUS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_TYPE_I_DIABETES_MELLITUS.html G6 SIG_BCR_SIGNALING_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/SIG_BCR_SIGNALING_PATHWAY.html G7 N/A http://stke.sciencemag.org/cgi/cm/stkecm;CMP_7918 G8 SA_B_CELL_RECEPTOR_COMPLEXES http://www.broadinstitute.org/gsea/msigdb/cards/SA_B_CELL_RECEPTOR_COMPLEXES.html G9 BIOCARTA_PROTEASOME_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_PROTEASOME_PATHWAY.html G10 BIOCARTA_TPO_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_TPO_PATHWAY.html G11 KEGG_ETHER_LIPID_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_ETHER_LIPID_METABOLISM.html G12 KEGG_CELL_ADHESION_MOLECULES_CAMS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_CELL_ADHESION_MOLECULES_CAMS.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S9c ClickTable.htm here to download Table: Table S9c.pdf 2/24/11 3:33 PM
Table S9c. Canonical pathways associated with case samples in GSAAzs-ks (CD) Sorted by FDR Index Description G1 N/A G2 Gi and Go proteins are members of the same family that transduce cellular signals through both their alpha and beta subunits. G3 N/A G4 Genes involved in aminoacyl-tRNA biosynthesis G5 Genes involved in type I diabetes mellitus G6 Members of the BCR signaling pathway G7 The fungus Dictyostelium discoideum is a model system for cytoskeletal organization during chemotaxis. G8 Antigen binding to B cell receptors activates protein tyrosine kinases, such as the Src family, which ultimate activate MAP kinases. G9 Ubiquitinated proteins are targeted for proteolytic degradation by the proteasome, where they are unfolded and degraded to small peptides in an ATP-dependent process. G10 Thrombopoietin binds to its receptor and activates cell growth through the Erk and JNK MAP kinase pathways, protein kinase C, and JAK/STAT activation. G11 Genes involved in ether lipid metabolism G12 Genes involved in cell adhesion molecules (CAMs)
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S9d Click here to download Table: Table S9d.pdf
Table S9d. Canonical pathways associated with case samples in GSAAzs-ks (CD)
Sorted by FDR
Index Genes
G1 PSMA1 PSMA2 PSMA3 PSMA4 PSMA5 PSMA6 PSMA7 PSMB1 PSMB10 PSMB2 PSMB3 PSMB4 PSMB5 PSMB6 PSMB7 PSMB8 PSMB9
G2 AKT1 AKT2 AKT3 ASAH1 BF BRAF DAG1 DRD2 EGFR EPHB2 GRB2 ITPKA ITPKB ITPR1 ITPR2 ITPR3 KCNJ3 KCNJ5 KCNJ9 MAPK1 PI3 PIK3CB PITX2 PLCB1 PLCB2 PLCB3 PLCB4 RAF1 RAP1GA1 RGS20 SHC1 SOS1 SOS2 SRC STAT3 TERF2IP
G3 AARS CARS DARS EPRS FARS2 FARSLB GARS HARS HARSL IARS KARS LARS LARS2 MARS MARS2 NARS QARS RARS SARS TARS WARS WARS2 YARS
G4 AARS AARS2 CARS CARS2 DARS DARS2 EARS2 EPRS FARS2 FARSA FARSB GARS HARS HARS2 IARS IARS2 KARS LARS LARS2 MARS MARS2 MTFMT NARS NARS2 PARS2 QARS RARS RARS2 SARS SARS2 TARS TARS2 VARS VARS2 WARS WARS2 YARS YARS2
G5 CD28 CD80 CD86 CPE FAS FASLG GAD1 GAD2 GZMB HLA-A HLA-A29.1 HLA-B HLA-C HLA-DMA HLA- DMB HLA-DOA HLA-DOB HLA-DPA1 HLA-DPB1 HLA-DQA1 HLA-DQA2 HLA-DQB1 HLA-DQB2 HLA-DRA HLA- DRB1 HLA-DRB3 HLA-DRB4 HLA-DRB5 HLA-E HLA-F HLA-G HSPD1 ICA1 IFNG IL12A IL12B IL1A IL1B IL2 INS LTA PRF1 PTPRN PTPRN2 TNF
G6 AKT1 AKT2 AKT3 BAD BCL2 BCR BLNK BTK CD19 CD22 CD81 CR2 CSK DAG1 FLOT1 FLOT2 GRB2 GSK3A GSK3B INPP5D ITPR1 ITPR2 ITPR3 LYN MAP4K1 MAPK1 MAPK3 NFATC1 NFATC2 NR0B2 PDK1 PIK3CA PIK3CD PIK3R1 PLCG2 PPP1R13B PPP3CA PPP3CB PPP3CC PTPRC RAF1 SHC1 SOS1 SOS2 SYK VAV1
G7 ACTR2 ACTR3 AKT1 ANGPTL2 BF DAG1 DGKA ETFA GCA ITGA9 ITPKA ITPKB ITPR1 ITPR2 ITPR3 MAP2K1 MAPK1 MAPK3 NR1I3 PAK1 PDE3A PDE3B PI3 PIK3C2G PIK3CA PIK3CD PIK3R1 PLDN PSME1 RIPK3 RPS4X SGCB VASP
G8 ATF2 BCR BLNK ELK1 FOS GRB2 HRAS JUN LYN MAP2K1 MAP3K1 MAPK1 MAPK3 MAPK8IP3 PAPPA RAC1 RPS6KA1 RPS6KA3 SHC1 SOS1 SYK VAV1 VAV2 VAV3 G9 PSMA1 PSMA2 PSMA3 PSMA4 PSMA5 PSMA6 PSMA7 PSMB1 PSMB2 PSMB3 PSMB4 PSMB5 PSMB6 PSMB7 PSMC3 PSMD14 RPN1 RPN2 UBE1 UBE2A UBE3A
G10 CSNK2A1 FOS GRB2 HRAS JAK2 JUN MAP2K1 MAPK3 MPL PIK3CA PIK3R1 PLCG1 PRKCA PRKCB1 RAF1 RASA1 SHC1 SOS1 STAT1 STAT3 STAT5A STAT5B THPO
G11 AGPAT1 AGPAT2 AGPAT3 AGPAT4 AGPAT6 AGPS CHPT1 ENPP2 ENPP6 LYCAT PAFAH1B1 PAFAH1B2 PAFAH1B3 PAFAH2 PLA2G10 PLA2G12A PLA2G12B PLA2G1B PLA2G2A PLA2G2D PLA2G2E PLA2G2F PLA2G3 PLA2G4A PLA2G5 PLA2G6 PLD1 PLD2 PPAP2A PPAP2B PPAP2C
G12 ALCAM CADM1 CADM3 CD2 CD22 CD226 CD274 CD276 CD28 CD34 CD4 CD40 CD40LG CD58 CD6 CD80 CD86 CD8A CD8B CD99 CDH1 CDH15 CDH2 CDH3 CDH4 CDH5 CLDN1 CLDN10 CLDN11 CLDN14 CLDN15 CLDN16 CLDN17 CLDN18 CLDN19 CLDN2 CLDN20 CLDN22 CLDN23 CLDN3 CLDN4 CLDN5 CLDN6 CLDN7 CLDN8 CLDN9 CNTN1 CNTN2 CNTNAP1 CNTNAP2 CTLA4 ESAM F11R GLG1 HLA-A HLA-A29.1 HLA-B HLA-C HLA-DMA HLA-DMB HLA-DOA HLA-DOB HLA- DPA1 HLA-DPB1 HLA-DQA1 HLA-DQA2 HLA-DQB1 HLA-DQB2 HLA-DRA HLA-DRB1 HLA-DRB3 HLA- DRB4 HLA-DRB5 HLA-E HLA-F HLA-G ICAM1 ICAM2 ICAM3 ICOS ICOSLG ITGA4 ITGA6 ITGA8 ITGA9 ITGAL ITGAM ITGAV ITGB1 ITGB2 ITGB7 ITGB8 JAM2 JAM3 L1CAM MADCAM1 MAG MPZ MPZL1 NCAM1 NCAM2 NEGR1 NEO1 NFASC NLGN1 NLGN2 NLGN3 NRCAM NRXN1 NRXN2 NRXN3 OCLN PDCD1 PDCD1LG2 PECAM1 PTPRC PTPRF PTPRM PVR PVRL1 PVRL2 PVRL3 SDC1 SDC2 SDC3 SDC4 SELE SELL SELP SELPLG SIGLEC1 SPN VCAM1 VCAN Table S10a ClickTable.htm here to download Table: Table S10a.pdf 2/24/11 2:08 PM
Table S10a. Canonical pathways associated with control samples in GSAAzs-ks (CD) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 ST_MYOCYTE_AD_PATHWAY 24 0 0.03676661 0.0565 G2 ST_WNT_CA2_CYCLIC_GMP_PATHWAY 18 0 0.041243922 0.0356 G3 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES 32 0 0.051279955 0.1069 G4 ST_GAQ_PATHWAY 26 0.00018423 0.06767928 0.1797 G5 HSA04730_LONG_TERM_DEPRESSION 66 0 0.10267447 0.4105 G6 SIG_CHEMOTAXIS 40 0 0.10358155 0.3685 G7 ST_ADRENERGIC 34 0 0.12181364 0.3633 G8 HSA02010_ABC_TRANSPORTERS_GENERAL 34 0.000374742 0.13926882 0.5536 G9 HSA04720_LONG_TERM_POTENTIATION 63 0.000194326 0.19322813 0.6954 G10 HSA04070_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 61 0.000384025 0.20259474 0.7423 G11 HSA04540_GAP_JUNCTION 75 0.000381025 0.21057452 0.8314 G12 GLYCINE_SERINE_AND_THREONINE_METABOLISM 31 0.00602306 0.22357273 0.8261 G13 HSA04320_DORSO_VENTRAL_AXIS_FORMATION 18 0.022837618 0.23480563 0.8157 G14 HSA00260_GLYCINE_SERINE_AND_THREONINE_METABOLISM 33 0.00990099 0.24446556 0.9096 G15 HSA04740_OLFACTORY_TRANSDUCTION 25 0.005400373 0.24564344 0.8986 G16 OVARIAN_INFERTILITY_GENES 23 0.010543537 0.2591639 0.8944 G17 CTLA4PATHWAY 16 0.046999652 0.2598574 0.9285 G18 PAR1PATHWAY 19 0.09219108 0.42805925 0.9917 G19 HSA03320_PPAR_SIGNALING_PATHWAY 52 0.015188548 0.43255928 0.9952 G20 PGC1APATHWAY 21 0.08320057 0.43309423 0.9941 G21 HSA04912_GNRH_SIGNALING_PATHWAY 81 0.003544005 0.4359843 0.9962 G22 HSA04360_AXON_GUIDANCE 97 5.87E-04 0.4445674 0.9935 G23 PTDINSPATHWAY 20 0.07875895 0.44761837 0.9917 G24 RARRXRPATHWAY 15 0.11111111 0.45251828 0.99 G25 NUCLEAR_RECEPTORS 37 0.009959778 0.4530905 0.9875 G26 RAC1PATHWAY 22 0.046306305 0.46745205 0.9869 G27 EGFPATHWAY 27 0.044150945 0.46878886 0.9985 G28 HSA04662_B_CELL_RECEPTOR_SIGNALING_PATHWAY 57 0.013875506 0.4791142 0.9984 G29 DCPATHWAY 18 0.1326423 0.49104926 0.9982 G30 HSA04520_ADHERENS_JUNCTION 67 0.013471301 0.5145631 0.9992 G31 GLEEVECPATHWAY 22 0.1043271 0.5183542 0.9993 G32 G_PROTEIN_SIGNALING 80 0.008400152 0.54036975 0.9996 G33 CHREBPPATHWAY 16 0.15879017 0.55092996 0.9995 G34 HSA04012_ERBB_SIGNALING_PATHWAY 78 0.01901652 0.5849707 0.9998 G35 HCMVPATHWAY 15 0.24386944 0.5965987 0.9998 G36 HSA00591_LINOLEIC_ACID_METABOLISM 20 0.20556228 0.6342666 1 G37 BADPATHWAY 22 0.14674012 0.67620933 1 G38 GPCRDB_CLASS_B_SECRETIN_LIKE 20 0.18117902 0.6828513 1 G39 HSA00071_FATTY_ACID_METABOLISM 39 0.17097013 0.6891736 1 G40 HSA00640_PROPANOATE_METABOLISM 26 0.17525585 0.68963623 1 G41 SIG_PIP3_SIGNALING_IN_CARDIAC_MYOCTES 62 0.084912956 0.69426525 1 G42 HSA00280_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 40 0.16226766 0.7009844 1 G43 HSA05223_NON_SMALL_CELL_LUNG_CANCER 50 0.09152608 0.7030152 1 G44 HSA00450_SELENOAMINO_ACID_METABOLISM 15 0.22922784 0.70968884 1 G45 GLUTAMATE_METABOLISM 19 0.21241662 0.7167437 1 G46 RHOPATHWAY 29 0.15664645 0.719036 1 G47 HSA04530_TIGHT_JUNCTION 100 0.023940345 0.72761196 1 G48 HSA04930_TYPE_II_DIABETES_MELLITUS 38 0.18891361 0.72852147 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 2:08 PM
G49 HSA00564_GLYCEROPHOSPHOLIPID_METABOLISM 41 0.11198617 0.7294694 1 G50 BIOPEPTIDESPATHWAY 36 0.10857033 0.7294738 1 G51 NITROGEN_METABOLISM 17 0.33979458 0.7336524 1 G52 PROPANOATE_METABOLISM 27 0.23074088 0.73417324 1 G53 SIG_INSULIN_RECEPTOR_PATHWAY_IN_CARDIAC_MYOCYTES 47 0.1470643 0.73683786 1 G54 HSA05214_GLIOMA 58 0.17300707 0.7377385 1 G55 HSA00910_NITROGEN_METABOLISM 19 0.30334798 0.74176633 1 G56 PTENPATHWAY 16 0.37519622 0.74861825 1 G57 HSA05211_RENAL_CELL_CARCINOMA 61 0.14997116 0.7505867 1 G58 CREBPATHWAY 26 0.22552255 0.7537097 1 G59 IL2PATHWAY 22 0.23241366 0.754775 1 G60 HSA00561_GLYCEROLIPID_METABOLISM 41 0.19977844 0.7580639 1 G61 HSA04742_TASTE_TRANSDUCTION 22 0.28879073 0.758913 1 G62 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY 31 0.26240742 0.7591332 1 G63 HSA00120_BILE_ACID_BIOSYNTHESIS 28 0.29549158 0.76230186 1 G64 HSA05030_AMYOTROPHIC_LATERAL_SCLEROSIS 17 0.32908666 0.76705563 1 G65 RASPATHWAY 22 0.2575307 0.7702973 1 G66 SIG_REGULATION_OF_THE_ACTIN_CYTOSKELETON_BY_RHO_GTPASES31 0.2674905 0.7727061 1 G67 CERAMIDEPATHWAY 22 0.35586855 0.774466 1 G68 NKCELLSPATHWAY 18 0.37888968 0.7769626 1 G69 ALANINE_AND_ASPARTATE_METABOLISM 17 0.37775907 0.77747667 1 G70 HSA00410_BETA_ALANINE_METABOLISM 22 0.3420248 0.77969503 1 G71 GLYCEROPHOSPHOLIPID_METABOLISM 40 0.24055971 0.7804312 1 G72 HSA00251_GLUTAMATE_METABOLISM 23 0.3130584 0.7901455 1 G73 GLYCEROLIPID_METABOLISM 37 0.29266986 0.7945279 1 G74 BUTANOATE_METABOLISM 24 0.38092652 0.7983727 1 G75 ECMPATHWAY 22 0.38844585 0.8019856 1 G76 HSA04350_TGF_BETA_SIGNALING_PATHWAY 78 0.19546351 0.80689585 1 G77 NO1PATHWAY 25 0.3570913 0.8070745 1 G78 HSA00632_BENZOATE_DEGRADATION_VIA_COA_LIGATION 15 0.41313022 0.80895776 1 G79 GLUTATHIONE_METABOLISM 19 0.42796123 0.8099694 1 G80 BETA_ALANINE_METABOLISM 23 0.39313743 0.81075317 1 G81 ST_GA12_PATHWAY 20 0.42391106 0.8113495 1 G82 BILE_ACID_BIOSYNTHESIS 24 0.4698407 0.8147696 1 G83 HSA00650_BUTANOATE_METABOLISM 32 0.37619397 0.8159331 1 G84 ST_JNK_MAPK_PATHWAY 38 0.41427767 0.8193085 1 G85 HSA04950_MATURITY_ONSET_DIABETES_OF_THE_YOUNG 17 0.42504 0.8206988 1 G86 HSA00600_SPHINGOLIPID_METABOLISM 24 0.44459102 0.82196957 1 G87 HSA04340_HEDGEHOG_SIGNALING_PATHWAY 39 0.3649136 0.8246366 1 G88 VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 33 0.41103604 0.8252665 1 G89 TYROSINE_METABOLISM 27 0.3934029 0.8270241 1 G90 PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 16 0.47764373 0.82852185 1 G91 HDACPATHWAY 28 0.43087053 0.8298843 1 G92 ERKPATHWAY 29 0.45282668 0.8316927 1 G93 CARDIACEGFPATHWAY 16 0.47603545 0.83224964 1 G94 STARCH_AND_SUCROSE_METABOLISM 23 0.519722 0.8347867 1 G95 GLYCOSPHINGOLIPID_METABOLISM 20 0.45238984 0.8362044 1 G96 HSA00310_LYSINE_DEGRADATION 30 0.5295122 0.8371327 1 G97 MEF2DPATHWAY 17 0.5506879 0.83749247 1 G98 BCRPATHWAY 33 0.44565633 0.8398071 1 G99 NOS1PATHWAY 21 0.46180305 0.8398364 1 G100 HSA05218_MELANOMA 58 0.46234068 0.8408835 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 2:08 PM
G101 ANDROGEN_AND_ESTROGEN_METABOLISM 18 0.5528357 0.84183246 1 G102 HSA05217_BASAL_CELL_CARCINOMA 35 0.52721155 0.84571326 1 G103 TCRPATHWAY 42 0.48057693 0.8478974 1 G104 MCALPAINPATHWAY 24 0.49322444 0.8484786 1 G105 HSA00860_PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 25 0.49351132 0.8490515 1 G106 IGF1MTORPATHWAY 19 0.5219322 0.8538527 1 G107 HSA00562_INOSITOL_PHOSPHATE_METABOLISM 36 0.5099177 0.85600424 1 G108 ALKPATHWAY 32 0.48092464 0.8574182 1 G109 HSA04916_MELANOGENESIS 78 0.4457737 0.85935605 1 G110 STATIN_PATHWAY_PHARMGKB 15 0.5403154 0.8623674 1 G111 HSA00620_PYRUVATE_METABOLISM 34 0.55056816 0.86374086 1 G112 ST_GRANULE_CELL_SURVIVAL_PATHWAY 24 0.6737132 0.8728854 1 G113 HSA00350_TYROSINE_METABOLISM 40 0.6435449 0.87770087 1 G114 CALCINEURINPATHWAY 17 0.67449605 0.8783777 1 G115 HSA05210_COLORECTAL_CANCER 73 0.6632296 0.8795354 1 G116 PHENYLALANINE_METABOLISM 19 0.6270231 0.87975127 1 G117 AT1RPATHWAY 33 0.63914025 0.88085645 1 G118 PYRUVATE_METABOLISM 33 0.6241885 0.8812689 1 G119 GLYCOLYSIS 47 0.6649648 0.8816509 1 G120 HSA05216_THYROID_CANCER 27 0.62063706 0.8825417 1 G121 PITX2PATHWAY 16 0.651138 0.8838574 1 G122 PYK2PATHWAY 26 0.7054677 0.8863423 1 G123 METPATHWAY 35 0.5609665 0.8865188 1 G124 GLYCOLYSIS_AND_GLUCONEOGENESIS 37 0.60626084 0.8872509 1 G125 NFATPATHWAY 46 0.58950967 0.88782436 1 G126 GLUCONEOGENESIS 47 0.6649648 0.88838106 1 G127 HSA00500_STARCH_AND_SUCROSE_METABOLISM 44 0.7088726 0.8886655 1 G128 HSA05213_ENDOMETRIAL_CANCER 46 0.6150587 0.8894863 1 G129 MTORPATHWAY 22 0.6109726 0.89033777 1 G130 P53HYPOXIAPATHWAY 18 0.6037567 0.89083594 1 G131 NGFPATHWAY 19 0.6515043 0.8908484 1 G132 HSA04150_MTOR_SIGNALING_PATHWAY 39 0.7297921 0.89201623 1 G133 HSA00361_GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 17 0.60060364 0.8927771 1 G134 LYSINE_DEGRADATION 26 0.6176033 0.8936831 1 G135 HSA00010_GLYCOLYSIS_AND_GLUCONEOGENESIS 51 0.7029527 0.8938899 1 G136 HSA00480_GLUTATHIONE_METABOLISM 22 0.65339804 0.8973418 1 G137 HSA00360_PHENYLALANINE_METABOLISM 22 0.5826393 0.8978088 1 G138 HSA00602_GLYCOSPHINGOLIPID_BIOSYNTHESIS_NEO_LACTOSERIES 18 0.7047124 0.9000486 1 G139 HSA00020_CITRATE_CYCLE 23 0.5897206 0.9024506 1 G140 TOB1PATHWAY 17 0.7292111 0.9062643 1 G141 STRIATED_MUSCLE_CONTRACTION 32 0.7840349 0.9147579 1 G142 SPRYPATHWAY 16 0.7190258 0.9148829 1 G143 HSA00903_LIMONENE_AND_PINENE_DEGRADATION 19 0.7569881 0.9188036 1 G144 ERK5PATHWAY 17 0.6992532 0.9215352 1 G145 SMALL_LIGAND_GPCRS 16 0.70876825 0.9224311 1 G146 GPCRPATHWAY 33 0.81056255 0.9232971 1 G147 HSA00980_METABOLISM_OF_XENOBIOTICS_BY_CYTOCHROME_P450 40 0.8148411 0.92511696 1 G148 UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS 15 0.7717908 0.9263295 1 G149 CITRATE_CYCLE_TCA_CYCLE 18 0.7024365 0.92714816 1 G150 KREBS_TCA_CYCLE 25 0.76903737 0.9273841 1 G151 PEPTIDE_GPCRS 59 0.81881326 0.927704 1 G152 HSA00150_ANDROGEN_AND_ESTROGEN_METABOLISM 30 0.80181515 0.92888504 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 2:08 PM
G153 MPRPATHWAY 23 0.7662579 0.92985153 1 G154 HSA00220_UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS 25 0.80189365 0.93005663 1 G155 HISTIDINE_METABOLISM 23 0.8317069 0.94094956 1 G156 SIG_CD40PATHWAYMAP 31 0.87240356 0.94232464 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S10b ClickTable.htm here to download Table: Table S10b.pdf 2/24/11 2:11 PM
Table S10b. Canonical pathways associated with control samples in GSAAzs-ks (CD) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 ST_MYOCYTE_AD_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_MYOCYTE_AD_PATHWAY.html G2 ST_WNT_CA2_CYCLIC_GMP_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_WNT_CA2_CYCLIC_GMP_PATHWAY.html G3 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES http://www.broadinstitute.org/gsea/msigdb/cards/SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES.html G4 ST_GAQ_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_GAQ_PATHWAY.html G5 KEGG_LONG_TERM_DEPRESSION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_LONG_TERM_DEPRESSION.html G6 SIG_CHEMOTAXIS http://www.broadinstitute.org/gsea/msigdb/cards/SIG_CHEMOTAXIS.html G7 ST_ADRENERGIC http://www.broadinstitute.org/gsea/msigdb/cards/ST_ADRENERGIC.html G8 KEGG_ABC_TRANSPORTERS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_ABC_TRANSPORTERS.html G9 KEGG_LONG_TERM_POTENTIATION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_LONG_TERM_POTENTIATION.html G10 KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM.html G11 KEGG_GAP_JUNCTION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GAP_JUNCTION.html G12 N/A N/A G13 KEGG_DORSO_VENTRAL_AXIS_FORMATION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_DORSO_VENTRAL_AXIS_FORMATION.html G14 KEGG_GLYCINE_SERINE_AND_THREONINE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GLYCINE_SERINE_AND_THREONINE_METABOLISM.html G15 KEGG_OLFACTORY_TRANSDUCTION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_OLFACTORY_TRANSDUCTION.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S10c ClickTable.htm here to download Table: Table S10c.pdf 2/24/11 2:13 PM
Table S10c. Canonical pathways associated with control samples in GSAAzs-ks (CD) Sorted by FDR Index Description G1 Cardiac myocytes have a variety of adrenergic receptors that induce subtype-specific signaling effects. G2 Some Wnt glycoprotein/Frizzled receptor interactions increase intracellular calcium and decrease cGMP. G3 Genes related to PIP3 signaling in B lymphocytes G4 G-alpha-q activates phospholipase C, resulting in calcium influx and increasing protein kinase C activity. G5 Genes involved in long-term depression G6 Genes related to chemotaxis G7 Adrenergic receptors respond to epinephrine and norepinephrine signaling. G8 Genes involved in ABC transporters - general G9 Genes involved in long-term potentiation G10 Genes involved in phosphatidylinositol signaling system G11 Genes involved in gap junction G12 N/A G13 Genes involved in dorso-ventral axis formation G14 Genes involved in glycine, serine and threonine metabolism G15 Genes involved in olfactory transduction
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S10d Click here to download Table: Table S10d.pdf
Table S10d. Canonical pathways associated with control samples in GSAAzs-ks (CD)
Sorted by FDR
Index Genes
G1 ADRB1 AKT1 APC ASAH1 BF CAMP CAV3 DAG1 DLG4 EPHB2 GAS GNAI1 GNAQ HTATIP ITPR1 ITPR2 ITPR3 KCNJ3 KCNJ5 KCNJ9 MAPK1 PITX2 PLB PTX1 PTX3 RAC1 RHO RYR1
G2 BF CAMK2A CAMK2B CAMK2D CAMK2G DAG1 ITPKA ITPKB ITPR1 ITPR2 ITPR3 NFAT5 PDE6A PDE6B PDE6C PDE6D PDE6G PDE6H SLC6A13 TF
G3 AKT1 AKT2 AKT3 BCR BTK CD19 CDKN2A DAPP1 FLOT1 FLOT2 FOXO3A GAB1 ITPR1 ITPR2 ITPR3 LYN NR0B2 P101-PI3K PDK1 PHF11 PIK3CA PITX2 PLCG2 PPP1R13B PREX1 PSCD3 PTEN PTPRC RPS6KA1 RPS6KA2 RPS6KA3 RPS6KB1 SAG SYK TEC VAV1
G4 ADRBK1 AKT1 AKT2 AKT3 BF DAG1 GNAQ IKBKG ITPKA ITPKB ITPR1 ITPR2 ITPR3 NFKB1 NFKB2 NFKBIA NFKBIB NFKBIE NFKBIL1 NFKBIL2 PDK1 PHKA2 PIK3CB PITX2 PLD1 PLD2 PLD3 VN1R1
G5 ARAF BRAF C7orf16 CACNA1A CRH CRHR1 GNA11 GNA12 GNA13 GNAI1 GNAI2 GNAI3 GNAO1 GNAQ GNAS GNAZ GRIA1 GRIA2 GRIA3 GRID2 GRM1 GRM5 GUCY1A2 GUCY1A3 GUCY1B3 GUCY2C GUCY2D GUCY2F HRAS IGF1 IGF1R ITPR1 ITPR2 ITPR3 KRAS LYN MAP2K1 MAP2K2 MAPK1 MAPK3 NOS1 NOS2A NOS3 NPR1 NPR2 NRAS PLA2G10 PLA2G12A PLA2G12B PLA2G1B PLA2G2A PLA2G2D PLA2G2E PLA2G2F PLA2G3 PLA2G4A PLA2G5 PLA2G6 PLCB1 PLCB2 PLCB3 PLCB4 PPP2CA PPP2CB PPP2R1A PPP2R1B PPP2R2A PPP2R2B PPP2R2C PRKCA PRKCB1 PRKCG PRKG1 PRKG2 RAF1 RYR1
G6 ACTR2 ACTR3 AKT1 AKT2 AKT3 ANGPTL2 ARHGAP1 ARHGAP4 ARHGEF11 BTK CDC42 CFL1 CFL2 GDI1 GDI2 INPPL1 ITPR1 ITPR2 ITPR3 LIMK1 MYLK MYLK2 P101-PI3K PAK1 PAK2 PAK3 PAK4 PAK6 PAK7 PDK1 PIK3CA PIK3CD PIK3CG PIK3R1 PITX2 PPP1R13B PTEN RACGAP1 RHO ROCK1 ROCK2 RPS4X SAG WASF1 WASL
G7 AKT1 APC AR ASAH1 BF BRAF CAMP CCL13 CCL15 CCL16 DAG1 EGFR GAS GNA11 GNA15 GNAI1 GNAQ ITPKA ITPKB ITPR1 ITPR2 ITPR3 KCNJ3 KCNJ5 KCNJ9 MAPK1 MAPK10 MAPK14 PHKA2 PIK3CA PIK3CD PIK3R1 PITX2 PTX1 PTX3 RAF1 SRC
G8 ABCA1 ABCA10 ABCA12 ABCA13 ABCA2 ABCA3 ABCA4 ABCA5 ABCA6 ABCA7 ABCA8 ABCA9 ABCB1 ABCB10 ABCB11 ABCB4 ABCB5 ABCB6 ABCB7 ABCB8 ABCB9 ABCC1 ABCC10 ABCC11 ABCC12 ABCC2 ABCC3 ABCC4 ABCC5 ABCC6 ABCC8 ABCC9 ABCD1 ABCD2 ABCD3 ABCD4 ABCG1 ABCG2 ABCG4 ABCG5 ABCG8 CFTR TAP1 TAP2 G9 ADCY1 ADCY8 ARAF ATF4 BRAF CACNA1C CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CAMK4 CHP CREBBP EP300 GNAQ GRIA1 GRIA2 GRIN1 GRIN2A GRIN2B GRIN2C GRIN2D GRM1 GRM5 HRAS ITPR1 ITPR2 ITPR3 KRAS MAP2K1 MAP2K2 MAPK1 MAPK3 NRAS PLCB1 PLCB2 PLCB3 PLCB4 PPP1CA PPP1CB PPP1CC PPP1R12A PPP1R1A PPP3CA PPP3CB PPP3CC PPP3R1 PPP3R2 PRKACA PRKACB PRKACG PRKCA PRKCB1 PRKCG PRKX PRKY RAF1 RAP1A RAP1B RAPGEF3 RPS6KA1 RPS6KA2 RPS6KA3 RPS6KA6
G10 CALM1 CALM2 CALM3 CALML3 CALML6 CARKL CDIPT CDS1 CDS2 DGKA DGKB DGKD DGKE DGKG DGKH DGKI DGKQ DGKZ FN3K IMPA1 IMPA2 INPP1 INPP4A INPP4B INPP5A INPP5B INPP5D INPP5E INPPL1 ITGB1BP3 ITPK1 ITPKA ITPKB ITPR1 ITPR2 ITPR3 OCRL PI4KA PI4KB PIB5PA PIK3C2A PIK3C2B PIK3C2G PIK3C3 PIK3CA PIK3CB PIK3CD PIK3CG PIK3R1 PIK3R2 PIK3R3 PIK3R5 PIP4K2A PIP4K2B PIP4K2C PIP5K1A PIP5K1B PIP5K1C PIP5K3 PLCB1 PLCB2 PLCB3 PLCB4 PLCD1 PLCD3 PLCD4 PLCE1 PLCG1 PLCG2 PLCZ1 PRKCA PRKCB1 PRKCG PTEN PTPMT1 SKIP SYNJ1 SYNJ2
G11 ADCY1 ADCY2 ADCY3 ADCY4 ADCY5 ADCY6 ADCY7 ADCY8 ADCY9 ADRB1 CDC2 CSNK1D DRD1 DRD2 EDG2 EGF EGFR GJA1 GJD2 GNA11 GNAI1 GNAI2 GNAI3 GNAQ GNAS GRB2 GRM1 GRM5 GUCY1A2 GUCY1A3 GUCY1B3 GUCY2C GUCY2D GUCY2F HRAS HTR2A HTR2B HTR2C ITPR1 ITPR2 ITPR3 KRAS LOC643224 LOC654264 MAP2K1 MAP2K2 MAP2K5 MAP3K2 MAPK1 MAPK3 MAPK7 NPR1 NPR2 NRAS PDGFA PDGFB PDGFC PDGFD PDGFRA PDGFRB PLCB1 PLCB2 PLCB3 PLCB4 PRKACA PRKACB PRKACG PRKCA PRKCB1 PRKCG PRKG1 PRKG2 PRKX PRKY RAF1 SOS1 SOS2 SRC TJP1 TUBA1A TUBA1B TUBA1C TUBA3C TUBA3D TUBA3E TUBA4A TUBA8 TUBAL3 TUBB TUBB1 TUBB2A TUBB2B TUBB2C TUBB3 TUBB4 TUBB4Q TUBB6 TUBB8 G12 ABP1 AGXT AGXT2 ALAS1 ALAS2 AMT AOC2 AOC3 ATP6V0C /// SHMT1 BHMT CBS CHDH CHKA CHKB CHKB /// CPT1B CTH DAO DLD DMGDH GAMT GARS GATM GCAT GLDC MAOA MAOB PEMT PISD PLCB2 PLCG1 PLCG2 PSPH SARDH SARS SHMT1 SHMT2 TARS
G13 BRAF CPEB1 EGFR ERBB2 ERBB4 ETS1 ETS2 ETV6 ETV7 FMN2 GRB2 KRAS MAP2K1 MAPK1 MAPK3 NOTCH1 NOTCH2 NOTCH3 NOTCH4 PIWIL1 PIWIL2 PIWIL3 PIWIL4 RAF1 SOS1 SOS2 SPIRE1 SPIRE2
G14 ABP1 AGXT AGXT2 AKR1B10 ALAS1 ALAS2 AMT AOC2 AOC3 BHMT CBS CHDH CHKA CHKB CTH DAO DLD DMGDH GAMT GARS GATM GCAT GLDC GNMT HSD3B7 MAOA MAOB PEMT PHGDH PIPOX PISD PSAT1 PSPH RDH11 RDH12 RDH13 RDH14 SARDH SARS SARS2 SDS SHMT1 SHMT2 TARS TARS2
G15 ADCY3 ADRBK2 ARRB2 CALM1 CALM2 CALM3 CALML3 CALML6 CAMK2A CAMK2B CAMK2D CAMK2G CLCA1 CLCA2 CLCA4 CNGA3 CNGA4 CNGB1 GNAL GUCA1A GUCA1B GUCA1C PDC PDE1C PRKACA PRKACB PRKACG PRKG1 PRKG2 PRKX PRKY Table S11a ClickTable.htm here to download Table: Table S11a.pdf 2/24/11 1:49 PM
Table S11a. Canonical pathways associated with case samples in GSEA (CD) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 IL1RPATHWAY 28 0.009042335 0.21187428 0.6953 G2 BREAST_CANCER_ESTROGEN_SIGNALING 89 0.008585446 0.21339968 0.8315 G3 RELAPATHWAY 16 0.040978715 0.21382976 0.761 G4 HSA03050_PROTEASOME 22 0.027895695 0.21645766 0.7458 G5 HYPERTROPHY_MODEL 17 0.010233918 0.21892563 0.8254 G6 HSA04514_CELL_ADHESION_MOLECULES 97 0.027858026 0.2228336 0.8171 G7 HSA04612_ANTIGEN_PROCESSING_AND_PRESENTATION 57 0.028008299 0.22471209 0.7352 G8 PROTEASOMEPATHWAY 21 0.0419763 0.22573519 0.8059 G9 AMINOACYL_TRNA_BIOSYNTHESIS 17 0.018251875 0.22678804 0.6872 G10 APOPTOSIS 63 0.05631504 0.22712801 0.8534 G11 SA_MMP_CYTOKINE_CONNECTION 15 0.026348809 0.22715859 0.8698 G12 HSA05120_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTION 56 0.019696347 0.2275982 0.8857 G13 NO2IL12PATHWAY 15 0.050253294 0.2322961 0.8823 G14 NFKBPATHWAY 22 0.04784013 0.23309332 0.8663 G15 MRNA_PROCESSING_REACTOME 96 0.053911634 0.23996669 0.8049 G16 HSA00530_AMINOSUGARS_METABOLISM 17 0.055982653 0.24157642 0.901 G17 NTHIPATHWAY 21 0.002258727 0.24795309 0.6815 G18 ERYTHPATHWAY 15 0.026153212 0.25732175 0.9145 G19 HSA05110_CHOLERA_INFECTION 33 0.046125077 0.26705605 0.9278 G20 IL3PATHWAY 15 0.07611599 0.27090117 0.9492 G21 TIDPATHWAY 17 0.087944664 0.27226707 0.9446 G22 HIVNEFPATHWAY 51 0.042886596 0.27598718 0.9275 G23 ST_INTERLEUKIN_4_PATHWAY 24 0.054885402 0.27636778 0.9546 G24 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY 87 0.006592501 0.27737224 0.6799 G25 HSA04610_COMPLEMENT_AND_COAGULATION_CASCADES 61 0.023021001 0.27738574 0.9487 G26 PROTEASOME 15 0.04277857 0.27794933 0.9432 G27 ST_FAS_SIGNALING_PATHWAY 52 0.04618189 0.28018653 0.9535 G28 APOPTOSIS_GENMAPP 41 0.08366121 0.28157464 0.9597 G29 LAIRPATHWAY 15 0.029862793 0.28234112 0.9415 G30 CASPASEPATHWAY 21 0.06139459 0.28610757 0.9592 G31 STEMPATHWAY 15 0.015824085 0.28789988 0.9405 G32 HSA03030_DNA_POLYMERASE 16 0.07324162 0.29161966 0.9389 G33 HSA05219_BLADDER_CANCER 41 0.011183408 0.3092222 0.674 G34 TNFR2PATHWAY 18 0.053693984 0.317079 0.9691 G35 HSA04940_TYPE_I_DIABETES_MELLITUS 36 0.013758599 0.3239631 0.5251 G36 G1PATHWAY 25 0.0975025 0.3267946 0.9722 G37 INFLAMPATHWAY 28 0.10168794 0.32969955 0.9749 G38 CCR5PATHWAY 16 0.08448697 0.33081928 0.9742 G39 TYPE_III_SECRETION_SYSTEM 17 0.109135 0.33831045 0.9838 G40 NKTPATHWAY 26 0.13049853 0.34121522 0.9857 G41 IL6PATHWAY 21 0.015762538 0.34136716 0.6588 G42 PHOTOSYNTHESIS 18 0.11592434 0.3420021 0.9851 G43 HSA04115_P53_SIGNALING_PATHWAY 52 0.08761515 0.3431239 0.9789 G44 FLAGELLAR_ASSEMBLY 17 0.109135 0.34507668 0.9838 G45 ATRBRCAPATHWAY 17 0.1163072 0.34545967 0.9863 G46 PYRIMIDINE_METABOLISM 45 0.11896208 0.3488997 0.9784 G47 ST_TUMOR_NECROSIS_FACTOR_PATHWAY 27 0.13169056 0.35010746 0.9809 G48 CYTOKINEPATHWAY 20 0.100349575 0.35011926 0.9829 G49 TOLLPATHWAY 27 0.10014336 0.35023433 0.9889 G50 CELLCYCLEPATHWAY 23 0.12127317 0.35056433 0.9819 G51 ATP_SYNTHESIS 17 0.109135 0.35211903 0.9838 G52 HSA05131_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EPEC 33 0.121873125 0.35548934 0.9887 G53 HSA05130_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EHEC 33 0.121873125 0.36195278 0.9887
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 1:49 PM
G54 HSA04512_ECM_RECEPTOR_INTERACTION 73 0.15209581 0.3645771 0.9908 G55 P53PATHWAY 15 0.15653403 0.364836 0.9899 G56 CHOLESTEROL_BIOSYNTHESIS 15 0.21460177 0.3748015 0.993 G57 HSA05222_SMALL_CELL_LUNG_CANCER 83 0.14197658 0.37633148 0.9928 G58 HSA04110_CELL_CYCLE 98 0.15367793 0.3776427 0.9925 G59 ST_ERK1_ERK2_MAPK_PATHWAY 25 0.15258358 0.39341626 0.9946 G60 HSA00970_AMINOACYL_TRNA_BIOSYNTHESIS 19 0.01833199 0.39700043 0.6491 G61 HSA04640_HEMATOPOIETIC_CELL_LINEAGE 82 0.17065127 0.4076608 0.9956 G62 HSA00100_BIOSYNTHESIS_OF_STEROIDS 21 0.24192245 0.4085884 0.9954 G63 WNT_SIGNALING 49 0.13575025 0.41140345 0.996 G64 CELL_CYCLE_KEGG 76 0.17670926 0.4163768 0.9967 G65 HSA04670_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION 89 0.14579515 0.4168321 0.9965 G66 CALCINEURIN_NF_AT_SIGNALING 89 0.008237232 0.42792583 0.5226 G67 DNA_REPLICATION_REACTOME 39 0.21991618 0.42829457 0.9973 G68 ARAPPATHWAY 17 0.23466349 0.44068864 0.9979 G69 HSA00240_PYRIMIDINE_METABOLISM 57 0.20429891 0.44209614 0.9981 G70 G2PATHWAY 22 0.19893533 0.4455101 0.999 G71 CDMACPATHWAY 15 0.22583826 0.44732007 0.9985 G72 HSA01510_NEURODEGENERATIVE_DISEASES 35 0.14894488 0.45135716 0.999 G73 CHEMICALPATHWAY 20 0.21875 0.45180377 0.9987 G74 HSA00510_N_GLYCAN_BIOSYNTHESIS 24 0.22163048 0.45310768 0.999 G75 HSA05010_ALZHEIMERS_DISEASE 19 0.21091416 0.45367143 0.9991 G76 G1_TO_S_CELL_CYCLE_REACTOME 62 0.2313835 0.45605373 0.999 G77 TRANSLATION_FACTORS 39 0.20170736 0.46063703 0.9992 G78 CIRCADIAN_EXERCISE 39 0.23331267 0.4732479 0.9993 G79 UCALPAINPATHWAY 16 0.26674592 0.4830024 0.9993 G80 KERATINOCYTEPATHWAY 42 0.20750949 0.49013752 0.9996 G81 FASPATHWAY 26 0.23834617 0.49309447 0.9996 G82 IL2RBPATHWAY 34 0.24595535 0.49551317 0.9995 G83 TPOPATHWAY 23 0.23644729 0.49555525 0.9994 G84 INTEGRINPATHWAY 33 0.25906014 0.49683747 0.9996 G85 HSA00051_FRUCTOSE_AND_MANNOSE_METABOLISM 29 0.24877945 0.49736953 0.9996 G86 HSA04920_ADIPOCYTOKINE_SIGNALING_PATHWAY 62 0.1498219 0.49937505 0.9994 G87 GPCRDB_OTHER 34 0.24944094 0.50023943 0.9995 G88 FMLPPATHWAY 33 0.28532767 0.5063527 0.9996 G89 ATMPATHWAY 17 0.2516758 0.5159895 0.9997 G90 HSA04130_SNARE_INTERACTIONS_IN_VESICULAR_TRANSPORT 26 0.32900608 0.5178672 0.9997 G91 HSA05212_PANCREATIC_CANCER 70 0.26344302 0.5201331 0.9999 G92 IL12PATHWAY 20 0.27074325 0.5222479 0.9997 G93 HSA04664_FC_EPSILON_RI_SIGNALING_PATHWAY 64 0.28179044 0.5223337 0.9999 G94 ST_G_ALPHA_I_PATHWAY 33 0.24780388 0.52460444 0.9999 G95 DEATHPATHWAY 31 0.3250418 0.52749825 0.9999 G96 CCR3PATHWAY 22 0.26844835 0.5276354 0.9999 G97 ST_T_CELL_SIGNAL_TRANSDUCTION 39 0.3296146 0.53641814 0.9999 G98 ST_B_CELL_ANTIGEN_RECEPTOR 38 0.27615747 0.5396482 0.9999 G99 N_GLYCAN_BIOSYNTHESIS 17 0.3742268 0.55859905 1 G100 HSA05040_HUNTINGTONS_DISEASE 24 0.31962618 0.56301445 1 G101 PROSTAGLANDIN_AND_LEUKOTRIENE_METABOLISM 26 0.2742144 0.56324965 1 G102 GALACTOSE_METABOLISM 21 0.3192104 0.5634232 1 G103 HSA00790_FOLATE_BIOSYNTHESIS 27 0.35 0.57524395 1 G104 ST_GA13_PATHWAY 35 0.31867254 0.5798134 1 G105 INTRINSICPATHWAY 22 0.341251 0.58161944 1 G106 HSA04370_VEGF_SIGNALING_PATHWAY 58 0.34484175 0.5832635 1 G107 PROSTAGLANDIN_SYNTHESIS_REGULATION 24 0.38659793 0.5908615 1 G108 PPARAPATHWAY 49 0.35951024 0.59173894 1 G109 GSK3PATHWAY 23 0.43078783 0.5929054 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 1:49 PM
G110 CSKPATHWAY 21 0.40282828 0.5948963 1 G111 MAPKPATHWAY 79 0.4206687 0.5984846 1 G112 AMIPATHWAY 21 0.40282828 0.6002079 1 G113 HSA01430_CELL_COMMUNICATION 93 0.38267368 0.6023884 1 G114 SPPAPATHWAY 21 0.4163802 0.6053528 1 G115 EICOSANOID_SYNTHESIS 15 0.010490216 0.6212396 0.5141 G116 HSA04210_APOPTOSIS 75 0.45972335 0.62384397 1 G117 FRUCTOSE_AND_MANNOSE_METABOLISM 21 0.46903852 0.624772 1 G118 41BBPATHWAY 18 0.4608379 0.62879026 1 G119 UBIQUITIN_MEDIATED_PROTEOLYSIS 20 0.49793917 0.6572906 1 G120 HSA00252_ALANINE_AND_ASPARTATE_METABOLISM 23 0.46951604 0.6641993 1 G121 GHPATHWAY 27 0.46395752 0.67017907 1 G122 HSA05220_CHRONIC_MYELOID_LEUKEMIA 71 0.5040132 0.6713595 1 G123 ETSPATHWAY 16 0.5118297 0.67592716 1 G124 ACTINYPATHWAY 16 0.49105012 0.6774986 1 G125 MITOCHONDRIAPATHWAY 18 0.50345117 0.6784759 1 G126 HSA00590_ARACHIDONIC_ACID_METABOLISM 37 0.5198207 0.6826302 1 G127 APOPTOSIS_KEGG 46 0.008520366 0.6834375 0.3574 G128 TH1TH2PATHWAY 16 0.48430124 0.68349564 1 G129 ST_P38_MAPK_PATHWAY 32 0.53849244 0.7026191 1 G130 GCRPATHWAY 16 0.5704796 0.7072726 1 G131 HSA05221_ACUTE_MYELOID_LEUKEMIA 50 0.5449184 0.7075552 1 G132 PENTOSE_PHOSPHATE_PATHWAY 19 0.55102485 0.7093794 1 G133 CARBON_FIXATION 18 0.5219905 0.7103165 1 G134 HSA01030_GLYCAN_STRUCTURES_BIOSYNTHESIS_1 52 0.5600659 0.7103388 1 G135 HSA00052_GALACTOSE_METABOLISM 24 0.5592857 0.710342 1 G136 HSA00710_CARBON_FIXATION 19 0.54761904 0.7120884 1 G137 HSA00330_ARGININE_AND_PROLINE_METABOLISM 26 0.564333 0.7129193 1 G138 TNFR1PATHWAY 27 0.52008885 0.713431 1 G139 BLOOD_CLOTTING_CASCADE 19 0.56219906 0.7142969 1 G140 PURINE_METABOLISM 97 0.59719753 0.72675514 1 G141 RACCYCDPATHWAY 22 0.60606676 0.753484 1 G142 STRESSPATHWAY 24 0.6581265 0.7580459 1 G143 CK1PATHWAY 16 0.669428 0.7598339 1 G144 SIG_IL4RECEPTOR_IN_B_LYPHOCYTES 26 0.6356507 0.76014596 1 G145 HSA04660_T_CELL_RECEPTOR_SIGNALING_PATHWAY 84 0.62201726 0.76082236 1 G146 INTEGRIN_MEDIATED_CELL_ADHESION_KEGG 78 0.6259252 0.7612612 1 G147 HSA05050_DENTATORUBROPALLIDOLUYSIAN_ATROPHY 15 0.6327954 0.7619302 1 G148 HSA00380_TRYPTOPHAN_METABOLISM 42 0.6485825 0.7628631 1 G149 ST_INTEGRIN_SIGNALING_PATHWAY 72 0.6670747 0.76289636 1 G150 VEGFPATHWAY 26 0.63865715 0.7643784 1 G151 IGF1RPATHWAY 15 0.6584507 0.7661872 1 G152 HSA00030_PENTOSE_PHOSPHATE_PATHWAY 21 0.6331533 0.7670071 1 G153 PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 83 0.7301975 0.79347557 1 G154 HSA00565_ETHER_LIPID_METABOLISM 19 0.73873335 0.8051771 1 G155 HSA05215_PROSTATE_CANCER 80 0.72193927 0.8101167 1 G156 HSA01032_GLYCAN_STRUCTURES_DEGRADATION 21 0.7204882 0.8264841 1 G157 HSP27PATHWAY 15 0.76001596 0.834891 1 G158 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_CHEMOTAXIS_PATHWAY 29 0.7550444 0.8477846 1 G159 PDGFPATHWAY 27 0.76161736 0.86398065 1 G160 RNA_TRANSCRIPTION_REACTOME 29 0.8012158 0.8730732 1 G161 IL7PATHWAY 16 0.7915034 0.8984277 1 G162 CARM_ERPATHWAY 24 0.8504451 0.90017575 1 G163 VIPPATHWAY 25 0.8215768 0.9146164 1 G164 TELPATHWAY 15 0.81565255 0.91635233 1 G165 FCER1PATHWAY 36 0.85778046 0.91749686 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 1:49 PM
G166 TRYPTOPHAN_METABOLISM 47 0.83713424 0.91874254 1 G167 IGF1PATHWAY 20 0.8075495 0.9208147 1 G168 SIG_BCR_SIGNALING_PATHWAY 43 0.9008734 0.92432106 1 G169 INSULINPATHWAY 21 0.8513679 0.92527413 1 G170 P38MAPKPATHWAY 39 0.83750504 0.9366167 1 G171 ARGININE_AND_PROLINE_METABOLISM 38 0.85195374 0.94195926 1 G172 SA_B_CELL_RECEPTOR_COMPLEXES 23 0.92378473 0.9420934 1 G173 WNTPATHWAY 23 0.9318898 0.9671948 1 G174 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS 27 0.8820065 0.9708925 1 G175 INOSITOL_PHOSPHATE_METABOLISM 22 0.9440981 0.97116977 1 G176 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS 41 0.9072375 0.98096114 1 G177 EPOPATHWAY 19 0.94323575 0.98379743 1 G178 EIF4PATHWAY 23 0.91167516 0.9845609 1 G179 HSA03022_BASAL_TRANSCRIPTION_FACTORS 25 0.994929 0.9945742 1 G180 CXCR4PATHWAY 23 0.9761468 0.99781656 1 G181 AKTPATHWAY 17 0.9521319 1 1 G182 EDG1PATHWAY 24 0.97275317 1 1 G183 HSA04330_NOTCH_SIGNALING_PATHWAY 32 0.98575103 1 1 G184 NDKDYNAMINPATHWAY 15 0.97038364 1 1 G185 RIBOSOMAL_PROTEINS 77 0.97520334 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S11b ClickTable.htm here to download Table: Table S11b.pdf 2/24/11 1:51 PM
Table S11b. Canonical pathways associated with case samples in GSEA (CD) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 BIOCARTA_IL1R_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_IL1R_PATHWAY.html G2 N/A N/A G3 BIOCARTA_RELA_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_RELA_PATHWAY.html G4 KEGG_PROTEASOME http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PROTEASOME.html G5 N/A N/A G6 KEGG_CELL_ADHESION_MOLECULES_CAMS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_CELL_ADHESION_MOLECULES_CAMS.html G7 KEGG_ANTIGEN_PROCESSING_AND_PRESENTATION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_ANTIGEN_PROCESSING_AND_PRESENTATION.html G8 BIOCARTA_PROTEASOME_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_PROTEASOME_PATHWAY.html G9 KEGG_AMINOACYL_TRNA_BIOSYNTHESIS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_AMINOACYL_TRNA_BIOSYNTHESIS.html G10 KEGG_APOPTOSIS http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_APOPTOSIS.html G11 SA_MMP_CYTOKINE_CONNECTION http://www.broadinstitute.org/gsea/msigdb/cards/SA_MMP_CYTOKINE_CONNECTION.html G12 KEGG_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTION http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTION.html G13 BIOCARTA_NO2IL12_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NO2IL12_PATHWAY.html G14 N/A http://www.biocarta.com/pathfiles/h_nfkbPathway.asp G15 N/A N/A G16 N/A N/A G17 BIOCARTA_NTHI_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_NTHI_PATHWAY.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S11c ClickTable.htm here to download Table: Table S11c.pdf 2/24/11 2:02 PM
Table S11c. Canonical pathways associated with case samples in GSEA (CD) Sorted by FDR Index Description G1 The cytokine IL-1 stimulates its primary receptor, IL-1R1, which induces transcription of inflammation-related genes such as interferons. G2 Genes preferentially expressed in breast cancers, especially those involved in estrogen-receptor-dependent signal transduction. G3 Acetylated NF-kB proteins are immune to IkB regulation and promote transcription until the histone deacetylase HDAC3 deacetylates the RelA subunit of NF-kB. G4 Genes involved in proteasome G5 N/A G6 Genes involved in cell adhesion molecules (CAMs) G7 Genes involved in antigen processing and presentation G8 Ubiquitinated proteins are targeted for proteolytic degradation by the proteasome, where they are unfolded and degraded to small peptides in an ATP-dependent process. G9 N/A G10 N/A G11 Cytokines can induce activation of matrix metalloproteinases, which degrade extracellular matrix. G12 Genes involved in epithelial cell signaling in Helicobacter pylori infection G13 Macrophages activate NK cells by releasing IL-12, which induces NK cytotoxic activity in coordination with NO produced by inducible nitric oxide synthase II. G14 Inactive nuclear factor kB (NF-kB) is inhibited by the IkB family in the cytoplasm; active NF-kB is localized in the nucleus and regulates transcription of a variety of genes. G15 N/A G16 Genes involved in aminosugars metabolism G17 Hemophilus influenzae infections activate NF-kB via several pathways, inducing the inflammatory response.
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S11d Click here to download Table: Table S11d.pdf
Table S11d. Canonical pathways associated with case samples in GSEA (CD)
Sorted by FDR
Index Genes
G1 CHUK IFNA1 IFNB1 IKBKB IL1A IL1B IL1R1 IL1RAP IL1RN IL6 IRAK1 IRAK2 IRAK3 JUN MAP2K3 MAP2K6 MAP3K1 MAP3K14 MAP3K7 MAP3K7IP1 MAPK14 MAPK8 MYD88 NFKB1 NFKBIA RELA SITPEC TGFB1 TGFB2 TGFB3 TNF TOLLIP TRAF6
G2 ACTB AR ATF2 AZGP1 BAD BAG1 BCL2 BCL2L2 BPAG1 C3 CCNA1 CCNA2 CCND1 CCNE1 CCNE2 CD44 CDH1 CDKN1A CDKN1B CDKN2A CLDN7 CLU COL6A1 CTNNB1 CTSB CTSD CYP19A1 DLC1 EGFR ERBB2 ESR1 ESR2 F3 FGF1 FHL5 FLRT1 FOSL1 GABRP GAPD GATA3 GNAS GSN HMGB1 HSPB1 ID2 IGFBP2 IL2RA IL6 IL6R IL6ST ITGA6 ITGB4 JUN KIT KLF5 KLK5 KRT18 KRT19 KRTHB6 MAP2K7 MKI67 MLP MT3 MUC1 NFYB NGFB NGFR NME1 PAPPA PGR PLAU PPIA PPP1R15A PTEN PTGS2 RAC2 RPL13A RPL27 S100A2 SCGB1D2 SCGB2A1 SCGB2A2 SERPINA3 SERPINB5 SERPINE1 SLC7A5 SPRR1B STC2 TFF1 TFF3 TGFA THBS1 THBS2 THBS4 TIE TNFAIP2 TNFRSF6 TNFSF6 TOP2A TP53 VEGF
G3 CHUK CREBBP EP300 FADD HDAC3 IKBKB IKBKG NFKB1 NFKBIA RELA RIPK1 TNF TNFRSF1A TNFRSF1B TRADD TRAF6
G4 PSMA1 PSMA2 PSMA3 PSMA4 PSMA5 PSMA6 PSMA7 PSMB1 PSMB2 PSMB3 PSMB4 PSMB5 PSMB6 PSMB7 PSMC2 PSMC3 PSMD1 PSMD11 PSMD12 PSMD13 PSMD2 PSMD6
G5 ADAM10 ANKRD1 ATF3 CYR61 DUSP14 EIF4E EIF4EBP1 GDF8 HBEGF IFNG IFRD1 IL18 IL1A IL1R1 JUND MYOG NR4A3 TCF8 VEGF WDR1
G6 ALCAM CADM1 CADM3 CD2 CD22 CD226 CD274 CD276 CD28 CD34 CD4 CD40 CD40LG CD58 CD6 CD80 CD86 CD8A CD8B CD99 CDH1 CDH15 CDH2 CDH3 CDH4 CDH5 CLDN1 CLDN10 CLDN11 CLDN14 CLDN15 CLDN16 CLDN17 CLDN18 CLDN19 CLDN2 CLDN20 CLDN22 CLDN23 CLDN3 CLDN4 CLDN5 CLDN6 CLDN7 CLDN8 CLDN9 CNTN1 CNTN2 CNTNAP1 CNTNAP2 CTLA4 ESAM F11R GLG1 HLA-A HLA- A29.1 HLA-B HLA-C HLA-DMA HLA-DMB HLA-DOA HLA-DOB HLA-DPA1 HLA-DPB1 HLA-DQA1 HLA-DQA2 HLA-DQB1 HLA-DQB2 HLA-DRA HLA-DRB1 HLA-DRB3 HLA-DRB4 HLA-DRB5 HLA-E HLA-F HLA-G ICAM1 ICAM2 ICAM3 ICOS ICOSLG ITGA4 ITGA6 ITGA8 ITGA9 ITGAL ITGAM ITGAV ITGB1 ITGB2 ITGB7 ITGB8 JAM2 JAM3 L1CAM MADCAM1 MAG MPZ MPZL1 NCAM1 NCAM2 NEGR1 NEO1 NFASC NLGN1 NLGN2 NLGN3 NRCAM NRXN1 NRXN2 NRXN3 OCLN PDCD1 PDCD1LG2 PECAM1 PTPRC PTPRF PTPRM PVR PVRL1 PVRL2 PVRL3 SDC1 SDC2 SDC3 SDC4 SELE SELL SELP SELPLG SIGLEC1 SPN VCAM1 VCAN G7 B2M CALR CANX CD4 CD74 CD8A CD8B CIITA CREB1 CTSB CTSL1 CTSS HLA-A HLA- A29.1 HLA-B HLA-C HLA-DMA HLA-DMB HLA-DOA HLA-DOB HLA-DPA1 HLA-DPB1 HLA-DQA1 HLA-DQA2 HLA-DQB1 HLA-DQB2 HLA-DRA HLA-DRB1 HLA-DRB3 HLA-DRB4 HLA-DRB5 HLA-E HLA-F HLA-G HSP90AA1 HSP90AB1 HSPA5 IFI30 IFNA1 IFNA10 IFNA13 IFNA14 IFNA16 IFNA17 IFNA2 IFNA21 IFNA4 IFNA5 IFNA6 IFNA7 IFNA8 KIR2DL1 KIR2DL2 KIR2DL3 KIR2DL4 KIR2DL5A KIR2DS1 KIR2DS2 KIR2DS3 KIR2DS4 KIR2DS5 KIR3DL1 KIR3DL2 KIR3DL3 KLRC1 KLRC2 KLRC3 KLRC4 KLRD1 LGMN LTA NFYA NFYB NFYC PDIA3 PSME1 PSME2 RFX5 RFXANK RFXAP TAP1 TAP2 TAPBP
G8 PSMA1 PSMA2 PSMA3 PSMA4 PSMA5 PSMA6 PSMA7 PSMB1 PSMB2 PSMB3 PSMB4 PSMB5 PSMB6 PSMB7 PSMC3 PSMD14 RPN1 RPN2 UBE1 UBE2A UBE3A
G9 AARS CARS DARS EPRS FARS2 FARSLB GARS HARS HARSL IARS KARS LARS LARS2 MARS MARS2 NARS QARS RARS SARS TARS WARS WARS2 YARS
G10 APAF1 BAD BAK1_///_BCL2L7P1 BAX BCL2 BCL2L1 BCL2L11 BID BIRC2 BIRC3 BIRC4 BIRC5 BNIP3L CASP1 CASP10 CASP1_///_COPl CASP2 CASP3 CASP4 CASP6 CASP7 CASP8 CASP9 CHUK CYCS DFFA DFFB FADD FAS FASLG GZMB HELLS HRK IKBKB IKBKG IRF1 IRF2 IRF3 IRF4 IRF5 IRF6 IRF7 JUN LTA MAP2K4 MAP3K1 MAPK10 MDM2 MYC NFKB1 NFKBIA NFKBIB NFKBIE PRF1 RELA RIPK1 TNF TNFRSF10B TNFRSF1A TNFRSF1B TNFRSF21 TNFRSF25 TNFRSF25_///_PLEKHG5 TNFSF10 TP53 TP73 TRADD TRAF1 TRAF2 TRAF3
G11 ACE CD44 CSF1 FCGR3A IL1B IL6R SELL SPN TGFB1 TGFB2 TNF TNFRSF1A TNFRSF1B TNFRSF8 TNFSF8
G12 ADAM10 ADAM17 ATP6AP1 ATP6V0A1 ATP6V0A2 ATP6V0A4 ATP6V0B ATP6V0C ATP6V0D1 ATP6V0D2 ATP6V0E1 ATP6V1A ATP6V1B1 ATP6V1B2 ATP6V1C1 ATP6V1C2 ATP6V1D ATP6V1E1 ATP6V1E2 ATP6V1F ATP6V1G1 ATP6V1G2 ATP6V1G3 ATP6V1H CASP3 CCL5 CDC42 CHUK CSK CXCL1 EGFR F11R GIT1 HBEGF IGSF5 IKBKB IKBKG IL8 IL8RA IL8RB JAM2 JAM3 JUN LYN MAP2K4 MAP3K14 MAPK10 MAPK11 MAPK12 MAPK13 MAPK14 MAPK8 MAPK9 MET NFKB1 NFKB2 NFKBIA NOD1 PAK1 PLCG1 PLCG2 PTPN11 PTPRZ1 RAC1 RELA SRC TCIRG1 TJP1
G13 CCR5 CD2 CD3D CD3E CD3G CD3Z CD4 CXCR3 IFNG IL12A IL12B IL12RB1 IL12RB2 JAK2 NOS2A STAT4 TYK2 G14 CHUK FADD IKBKB IKBKG IL1A IL1R1 IRAK1 MAP3K1 MAP3K14 MAP3K7 MAP3K7IP1 MYD88 NFKB1 NFKBIA RELA RIPK1 TLR4 TNF TNFAIP3 TNFRSF1A TNFRSF1B TRADD TRAF6
G15 BRUNOL4 C10orf9 C20orf14 CD2BP2 CDC40 CLK2 CLK3 CLK4 COL2A1 CPSF1 CPSF2 CPSF3 CPSF4 CSTF1 CSTF2 CSTF2T CSTF3 CUGBP1 CUGBP2 DDIT3 DDX1 DDX20 DHX15 DHX16 DHX38 DHX8 DHX9 DICER1 DNAJC8 FLJ10748 FNBP3 FUS FUSIP1 GIPC1 HEAB HNRPA2B1 HNRPA3 HNRPA3P1 /// HNRPA3 /// LOC387933 HNRPA3P1 /// HNRPA3 /// LOC389395 HNRPAB HNRPC HNRPC /// HNRPCL1 /// LOC390615 /// LOC440563 HNRPD HNRPH1 HNRPH2 HNRPL HNRPR HNRPU HRMT1L2 LSM2 LSM7 METTL3 NCBP1 NCBP2 NONO NUDT21 NXF1 PABPN1 PAPOLA PHF5A POLR2A PPM1G PRPF18 PRPF3 PRPF4 PRPF4B PRPF8 PSKH1 PTBP1 PTBP2 RBM17 RBM5 RNGTT RNMT RNPC2 RNPS1 SF3A1 SF3A2 SF3A3 SF3B1 SF3B2 SF3B4 SF3B5 SF4 SFRS10 SFRS12 SFRS14 SFRS16 SFRS2 SFRS4 SFRS5 SFRS6 SFRS7 SFRS8 SFRS9 SMC1L1 SNRP70 SNRPA SNRPA1 SNRPB SNRPB2 SNRPD1 SNRPD2 SNRPD3 SNRPE SNRPF SNRPG SNRPN SNRPN /// PAR1 SNRPN /// SNURF SPOP SRPK1 SRPK2 SRRM1 SUPT5H TMP21 TXNL4A U2AF1 U2AF2 WDR57 XRN2
G16 AMDHD2 CHIA CHIT1 CMAS CTBS CYB5R1 CYB5R3 GFPT1 GFPT2 GNE GNPDA1 GNPDA2 GNPNAT1 HEXA HEXB HK1 HK2 HK3 LHPP MTMR1 MTMR2 MTMR6 NAGK NANS NPL PGM3 PHPT1 RENBP UAP1
G17 CHUK CREBBP DUSP1 EP300 IKBKB IL1B IL8 MADH3 MADH4 MAP2K3 MAP2K6 MAP3K14 MAP3K7 MAPK11 MAPK14 MYD88 NFKB1 NFKBIA NR3C1 RELA TGFBR1 TGFBR2 TLR2 TNF Table S12a ClickTable.htm here to download Table: Table S12a.pdf 2/24/11 1:37 PM
Table S12a. Canonical pathways associated with control samples in GSEA (CD) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 ST_WNT_CA2_CYCLIC_GMP_PATHWAY 18 0.002236682 0.07925691 0.0675 G2 HSA00310_LYSINE_DEGRADATION 30 0.027408144 0.28553036 0.7511 G3 LYSINE_DEGRADATION 26 0.019131128 0.31915477 0.8018 G4 BUTANOATE_METABOLISM 24 0.030787684 0.32249904 0.7482 G5 NUCLEAR_RECEPTORS 37 0.03472361 0.34616143 0.8569 G6 TYROSINE_METABOLISM 27 0.033858728 0.3462924 0.8379 G7 PGC1APATHWAY 21 0.022636218 0.36632442 0.7414 G8 HSA00632_BENZOATE_DEGRADATION_VIA_COA_LIGATION 15 0.051805016 0.42047948 0.8994 G9 HSA04740_OLFACTORY_TRANSDUCTION 25 0.025963489 0.4227559 0.7305 G10 BILE_ACID_BIOSYNTHESIS 24 0.00969697 0.4269891 0.6753 G11 HSA00120_BILE_ACID_BIOSYNTHESIS 28 0.011343284 0.4858537 0.629 G12 PHENYLALANINE_METABOLISM 19 0.05634594 0.4874644 0.9249 G13 HSA00561_GLYCEROLIPID_METABOLISM 41 0.062124625 0.56722313 0.9637 G14 HSA04950_MATURITY_ONSET_DIABETES_OF_THE_YOUNG 17 0.06095163 0.56733394 0.9577 G15 HSA00650_BUTANOATE_METABOLISM 32 0.012314797 0.5700547 0.5544 G16 HSA00360_PHENYLALANINE_METABOLISM 22 0.08293613 0.58461416 0.9627 G17 ST_MYOCYTE_AD_PATHWAY 24 0.058693912 0.5884844 0.9557 G18 HSA05213_ENDOMETRIAL_CANCER 46 0.05182804 0.5930792 0.9468 G19 HSA00450_SELENOAMINO_ACID_METABOLISM 15 0.057548437 0.622655 0.9553 G20 HSA00910_NITROGEN_METABOLISM 19 0.05245154 0.6299795 0.981 G21 NITROGEN_METABOLISM 17 0.04876176 0.63845354 0.9784 G22 ST_ADRENERGIC 34 0.09166174 0.664391 0.9784 G23 SIG_CHEMOTAXIS 40 0.098680325 0.6748275 0.9843 G24 GLYCEROLIPID_METABOLISM 37 0.09847534 0.6931543 0.9881 G25 HSA00280_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 40 0.120335266 0.6945732 0.9784 G26 HSA00340_HISTIDINE_METABOLISM 27 0.12807359 0.7084168 0.9874 G27 HISTIDINE_METABOLISM 23 0.10458911 0.72394127 0.9782 G28 HSA00903_LIMONENE_AND_PINENE_DEGRADATION 19 0.18343854 0.80444545 0.9917 G29 HSA00150_ANDROGEN_AND_ESTROGEN_METABOLISM 30 0.17277789 0.8232952 0.9941 G30 ANDROGEN_AND_ESTROGEN_METABOLISM 18 0.16819572 0.8237813 0.9931 G31 HSA00020_CITRATE_CYCLE 23 0.29373133 0.8402597 0.9993 G32 HSA05216_THYROID_CANCER 27 0.25381443 0.84243876 0.9986 G33 HSA04720_LONG_TERM_POTENTIATION 63 0.19025661 0.8431484 0.9984 G34 HSA00564_GLYCEROPHOSPHOLIPID_METABOLISM 41 0.1595092 0.8457446 0.9931 G35 HSA04930_TYPE_II_DIABETES_MELLITUS 38 0.20403764 0.85601634 0.9993 G36 PYK2PATHWAY 26 0.21955682 0.85846686 0.9984 G37 KREBS_TCA_CYCLE 25 0.29220393 0.8622737 0.9984 G38 PROPANOATE_METABOLISM 27 0.2840909 0.862807 0.999 G39 ERKPATHWAY 29 0.22912966 0.8639231 0.9983 G40 ST_GA12_PATHWAY 20 0.27337277 0.86560637 0.9992 G41 HSA04150_MTOR_SIGNALING_PATHWAY 39 0.25445706 0.86575073 0.9996 G42 HSA04012_ERBB_SIGNALING_PATHWAY 78 0.31327432 0.8724199 0.9998 G43 PITX2PATHWAY 16 0.30932704 0.87245464 0.9997 G44 HSA04320_DORSO_VENTRAL_AXIS_FORMATION 18 0.23169 0.87358546 0.9983 G45 GLYCINE_SERINE_AND_THREONINE_METABOLISM 31 0.27463794 0.8777414 0.999 G46 VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 33 0.23306613 0.8925362 0.9983
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 1:37 PM
G47 HSA00350_TYROSINE_METABOLISM 40 0.17033398 0.8926477 0.9966 G48 HSA00361_GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 17 0.2801521 0.89538425 0.9983 G49 HSA04340_HEDGEHOG_SIGNALING_PATHWAY 39 0.30723011 0.8992455 1 G50 HSA00640_PROPANOATE_METABOLISM 26 0.37953007 0.90035474 1 G51 HSA00480_GLUTATHIONE_METABOLISM 22 0.34210092 0.9027438 1 G52 HSA04540_GAP_JUNCTION 75 0.32938704 0.9042374 1 G53 HSA05218_MELANOMA 58 0.29825604 0.9122854 1 G54 CARDIACEGFPATHWAY 16 0.36080587 0.9131097 1 G55 HDACPATHWAY 28 0.24199004 0.91505194 0.9978 G56 CITRATE_CYCLE_TCA_CYCLE 18 0.25426722 0.91632414 0.9983 G57 HSA00071_FATTY_ACID_METABOLISM 39 0.3068026 0.91774935 1 G58 HSA00260_GLYCINE_SERINE_AND_THREONINE_METABOLISM 33 0.18139455 0.9192154 0.9966 G59 HSA05217_BASAL_CELL_CARCINOMA 35 0.23409413 0.91993064 0.9981 G60 HSA00620_PYRUVATE_METABOLISM 34 0.3390747 0.92106277 1 G61 BIOPEPTIDESPATHWAY 36 0.7949691 0.9246077 1 G62 HSA04912_GNRH_SIGNALING_PATHWAY 81 0.8313012 0.9253548 1 G63 NFATPATHWAY 46 0.33811396 0.92861503 1 G64 OXIDATIVE_PHOSPHORYLATION 47 0.6994644 0.93084836 1 G65 SMALL_LIGAND_GPCRS 16 0.3153771 0.9312014 1 G66 HSA00980_METABOLISM_OF_XENOBIOTICS_BY_CYTOCHROME_P45040 0.21838649 0.9320723 0.9978 G67 BADPATHWAY 22 0.7480484 0.935005 1 G68 HSA00010_GLYCOLYSIS_AND_GLUCONEOGENESIS 51 0.78325564 0.9355493 1 G69 MONOAMINE_GPCRS 22 0.69032776 0.9405221 1 G70 TCRPATHWAY 42 0.77171314 0.9443209 1 G71 HSA00860_PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 25 0.7285433 0.9456298 1 G72 HSA02010_ABC_TRANSPORTERS_GENERAL 34 0.42386672 0.9471705 1 G73 RARRXRPATHWAY 15 0.38767597 0.94995403 1 G74 BETA_ALANINE_METABOLISM 23 0.3981698 0.9509573 1 G75 G_PROTEIN_SIGNALING 80 0.78328174 0.9515297 1 G76 HSA04350_TGF_BETA_SIGNALING_PATHWAY 78 0.80153906 0.9536077 1 G77 HSA04730_LONG_TERM_DEPRESSION 66 0.511076 0.9547709 1 G78 HSA04742_TASTE_TRANSDUCTION 22 0.386183 0.95659727 1 G79 IGF1MTORPATHWAY 19 0.7806742 0.9567316 1 G80 OVARIAN_INFERTILITY_GENES 23 0.84307814 0.95845944 1 G81 SA_PTEN_PATHWAY 16 0.69864106 0.960056 1 G82 HSA05210_COLORECTAL_CANCER 73 0.9273513 0.96097296 1 G83 NO1PATHWAY 25 0.7922281 0.9610233 1 G84 HSA04662_B_CELL_RECEPTOR_SIGNALING_PATHWAY 57 0.9078396 0.96104836 1 G85 PEPTIDE_GPCRS 59 0.48364297 0.9626485 1 G86 SIG_CD40PATHWAYMAP 31 0.5420012 0.96283495 1 G87 PTDINSPATHWAY 20 0.43834478 0.9635169 1 G88 SIG_PIP3_SIGNALING_IN_CARDIAC_MYOCTES 62 0.90156466 0.9648619 1 G89 MCALPAINPATHWAY 24 0.87291664 0.96509 1 G90 STATIN_PATHWAY_PHARMGKB 15 0.8932024 0.9660265 1 G91 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES 32 0.86436224 0.9669618 1 G92 GLEEVECPATHWAY 22 0.8650904 0.9672694 1 G93 HSA00410_BETA_ALANINE_METABOLISM 22 0.70623547 0.9675492 1 G94 ERK5PATHWAY 17 0.7490257 0.9675817 1 G95 RASPATHWAY 22 0.7045861 0.96768034 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 1:37 PM
G96 HSA04140_REGULATION_OF_AUTOPHAGY 23 0.4889868 0.9677929 1 G97 ALANINE_AND_ASPARTATE_METABOLISM 17 0.8615635 0.96823186 1 G98 NKCELLSPATHWAY 18 0.55448276 0.97053367 1 G99 GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 23 0.5789567 0.9710482 1 G100 GLYCOLYSIS_AND_GLUCONEOGENESIS 37 0.93768024 0.97111833 1 G101 HSA00500_STARCH_AND_SUCROSE_METABOLISM 44 0.4650143 0.97134876 1 G102 HSA04520_ADHERENS_JUNCTION 67 0.5405987 0.9714814 1 G103 HSA00562_INOSITOL_PHOSPHATE_METABOLISM 36 0.5325211 0.9714843 1 G104 MEF2DPATHWAY 17 0.8690894 0.9715287 1 G105 GLUTATHIONE_METABOLISM 19 0.8712804 0.97232175 1 G106 AT1RPATHWAY 33 0.46500903 0.97270614 1 G107 GLYCEROPHOSPHOLIPID_METABOLISM 40 0.41540605 0.9741574 1 G108 GLYCOSPHINGOLIPID_METABOLISM 20 0.49365795 0.97465456 1 G109 GLYCOLYSIS 47 0.76708186 0.97520965 1 G110 GPCRDB_CLASS_B_SECRETIN_LIKE 20 0.51881504 0.97618866 1 G111 HSA00602_GLYCOSPHINGOLIPID_BIOSYNTHESIS_NEO_LACTOSERIES 18 0.8537026 0.97640294 1 G112 HSA00600_SPHINGOLIPID_METABOLISM 24 0.47192138 0.97661006 1 G113 EGFPATHWAY 27 0.8842712 0.97683954 1 G114 MTORPATHWAY 22 0.52190924 0.9781132 1 G115 HSA05030_AMYOTROPHIC_LATERAL_SCLEROSIS 17 0.42578283 0.9792683 1 G116 ST_GAQ_PATHWAY 26 0.6237543 0.979358 1 G117 HSA04360_AXON_GUIDANCE 97 0.54648614 0.9809534 1 G118 HSA00591_LINOLEIC_ACID_METABOLISM 20 0.8706314 0.980986 1 G119 NGFPATHWAY 19 0.46589318 0.9814324 1 G120 P53HYPOXIAPATHWAY 18 0.47509804 0.98143464 1 G121 PTENPATHWAY 16 0.60688156 0.9822073 1 G122 RHOPATHWAY 29 0.5723517 0.98236656 1 G123 ECMPATHWAY 22 0.5110373 0.9823679 1 G124 GLUCONEOGENESIS 47 0.76708186 0.9833364 1 G125 CTLA4PATHWAY 16 0.9258458 0.9836881 1 G126 GLUTAMATE_METABOLISM 19 0.58089703 0.98463225 1 G127 ALKPATHWAY 32 0.4606987 0.9847039 1 G128 HSA01031_GLYCAN_STRUCTURES_BIOSYNTHESIS_2 40 0.688271 0.9849701 1 G129 ST_JNK_MAPK_PATHWAY 38 0.9140859 0.9850642 1 G130 UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS 15 0.65926164 0.98614526 1 G131 HSA00190_OXIDATIVE_PHOSPHORYLATION 84 0.90533125 0.98638505 1 G132 PYRUVATE_METABOLISM 33 0.48901758 0.98652196 1 G133 ST_WNT_BETA_CATENIN_PATHWAY 23 0.9920761 0.98781675 1 G134 CALCINEURINPATHWAY 17 0.95330274 0.9881589 1 G135 HSA00220_UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS 25 0.7683225 0.9887762 1 G136 MPRPATHWAY 23 0.977043 0.9890254 1 G137 ST_GRANULE_CELL_SURVIVAL_PATHWAY 24 0.9738799 0.98916477 1 G138 NOS1PATHWAY 21 0.9219262 0.9892383 1 G139 CREBPATHWAY 26 0.7077743 0.989565 1 G140 SA_TRKA_RECEPTOR 16 0.74378663 0.9898737 1 G141 SPRYPATHWAY 16 0.6122449 0.9901 1 G142 HSA05214_GLIOMA 58 0.59480214 0.9902293 1 G143 HSA04070_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 61 0.5202822 0.9904149 1 G144 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY 31 0.99009705 0.99127275 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 1:37 PM
G145 RAC1PATHWAY 22 0.60826576 0.99160165 1 G146 HSA03320_PPAR_SIGNALING_PATHWAY 52 0.6773403 0.99196786 1 G147 GPCRPATHWAY 33 0.93243796 0.9919765 1 G148 SIG_INSULIN_RECEPTOR_PATHWAY_IN_CARDIAC_MYOCYTES 47 0.7952271 0.9926756 1 G149 HSA04530_TIGHT_JUNCTION 100 0.6769049 0.9928812 1 G150 BCRPATHWAY 33 0.9956035 0.99407244 1 G151 SIG_REGULATION_OF_THE_ACTIN_CYTOSKELETON_BY_RHO_GTPASES31 0.97621876 0.9946519 1 G152 HSA03010_RIBOSOME 54 0.914983 0.99507666 1 G153 HSA00251_GLUTAMATE_METABOLISM 23 0.62297446 0.99678195 1 G154 STARCH_AND_SUCROSE_METABOLISM 23 0.62607396 0.99678236 1 G155 HSA05223_NON_SMALL_CELL_LUNG_CANCER 50 0.75718534 0.9971259 1 G156 DCPATHWAY 18 0.62193674 0.99791855 1 G157 HSA04916_MELANOGENESIS 78 0.73865414 0.99858904 1 G158 HCMVPATHWAY 15 0.7108553 0.99914706 1 G159 CERAMIDEPATHWAY 22 0.67709404 1 1 G160 CHREBPPATHWAY 16 0.6504897 1 1 G161 HSA05211_RENAL_CELL_CARCINOMA 61 0.71810496 1 1 G162 IL2PATHWAY 22 0.633486 1 1 G163 METPATHWAY 35 0.9500496 1 1 G164 PAR1PATHWAY 19 0.9323558 1 1 G165 PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 16 0.6662766 1 1 G166 STRIATED_MUSCLE_CONTRACTION 32 0.69350964 1 1 G167 TOB1PATHWAY 17 0.74771374 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Table S12b ClickTable.htm here to download Table: Table S12b.pdf 2/24/11 1:40 PM
Table S12b. Canonical pathways associated with control samples in GSEA (CD) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 ST_WNT_CA2_CYCLIC_GMP_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_WNT_CA2_CYCLIC_GMP_PATHWAY.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S12c ClickTable.htm here to download Table: Table S12c.pdf 2/24/11 1:43 PM
Table S12c. Canonical pathways associated with control samples in GSEA (CD) Sorted by FDR Index Description G1 Some Wnt glycoprotein/Frizzled receptor interactions increase intracellular calcium and decrease cGMP.
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S12d Click here to download Table: Table S12d.pdf
Table S12d. Canonical pathways associated with control samples in GSEA (CD)
Sorted by FDR
Index Genes
G1 BF CAMK2A CAMK2B CAMK2D CAMK2G DAG1 ITPKA ITPKB ITPR1 ITPR2 ITPR3 NFAT5 PDE6A PDE6B PDE6C PDE6D PDE6G PDE6H SLC6A13 TF Table S13a ClickTable.htm here to download Table: Table S13a.pdf 2/24/11 1:26 PM
Table S13a. Canonical pathways associated with case or control samples in GSAA-SNP (CD) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 ST_GAQ_PATHWAY 20 0.0007 0.09499972 0.0828 G2 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_CHEMOTAXIS_PATHWAY 22 0.0011 0.15873586 0.327 G3 HSA00260_GLYCINE_SERINE_AND_THREONINE_METABOLISM 23 0.004 0.18863325 0.451 G4 ST_WNT_CA2_CYCLIC_GMP_PATHWAY 15 0.0047 0.1965493 0.2839 G5 SA_B_CELL_RECEPTOR_COMPLEXES 15 0.0132 0.21026708 0.5558 G6 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES 23 0.009 0.21460234 0.7581 G7 ST_MYOCYTE_AD_PATHWAY 19 0.0057 0.2314781 0.744 G8 ST_G_ALPHA_I_PATHWAY 27 0.0037 0.2617751 0.7408 G9 GLYCINE_SERINE_AND_THREONINE_METABOLISM 24 0.0069 0.26582387 0.6948 G10 SIG_BCR_SIGNALING_PATHWAY 33 0.0099 0.5069168 0.9656 G11 HSA04070_PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 49 0.0056 0.5797234 0.9829 G12 HSA04720_LONG_TERM_POTENTIATION 45 0.0084 0.62761277 0.9913 G13 ST_ADRENERGIC 27 0.0309 0.66211545 0.9959 G14 SIG_CHEMOTAXIS 30 0.0207 0.66675085 0.9971 G15 HSA04730_LONG_TERM_DEPRESSION 49 0.0098 0.6948486 0.9956 G16 HSA04540_GAP_JUNCTION 51 0.0095 0.7402898 0.9984 G17 41BBPATHWAY 16 0.9945 1 1 G18 ALKPATHWAY 23 0.919 1 1 G19 APOPTOSIS 44 0.9968 1 1 G20 APOPTOSIS_GENMAPP 28 0.9852 1 1 G21 APOPTOSIS_KEGG 31 0.8711 1 1 G22 ARGININE_AND_PROLINE_METABOLISM 27 0.9993 1 1 G23 AT1RPATHWAY 24 0.8724 1 1 G24 ATMPATHWAY 15 0.992 1 1 G25 ATRBRCAPATHWAY 16 0.9955 1 1 G26 BADPATHWAY 16 0.8681 1 1 G27 BCRPATHWAY 24 0.8354 1 1 G28 BETA_ALANINE_METABOLISM 18 0.9976 1 1 G29 BILE_ACID_BIOSYNTHESIS 19 0.9792 1 1 G30 BIOPEPTIDESPATHWAY 28 0.7017 1 1 G31 BREAST_CANCER_ESTROGEN_SIGNALING 65 0.9224 1 1 G32 BUTANOATE_METABOLISM 19 0.995 1 1 G33 CALCINEURIN_NF_AT_SIGNALING 63 0.9814 1 1 G34 CALCINEURINPATHWAY 15 0.6053 1 1 G35 CALCIUM_REGULATION_IN_CARDIAC_CELLS 73 0.3241 1 1 G36 CARM_ERPATHWAY 20 0.2641 1 1 G37 CASPASEPATHWAY 15 0.9876 1 1 G38 CCR3PATHWAY 15 0.5801 1 1 G39 CELL_CYCLE_KEGG 63 1 1 1 G40 CELLCYCLEPATHWAY 19 0.9798 1 1 G41 CERAMIDEPATHWAY 16 0.9468 1 1 G42 CHEMICALPATHWAY 16 0.9177 1 1 G43 CIRCADIAN_EXERCISE 29 0.9238 1 1 G44 CREBPATHWAY 19 0.4776 1 1 G45 CXCR4PATHWAY 18 0.9454 1 1 G46 DEATHPATHWAY 23 0.9883 1 1 G47 DNA_REPLICATION_REACTOME 29 1 1 1 G48 ECMPATHWAY 17 0.8855 1 1 G49 EDG1PATHWAY 18 0.5547 1 1 G50 EGFPATHWAY 19 0.4698 1 1 G51 EIF4PATHWAY 16 0.944 1 1 G52 ERKPATHWAY 19 0.5852 1 1 G53 FASPATHWAY 20 0.9686 1 1 G54 FCER1PATHWAY 24 0.9789 1 1 G55 FMLPPATHWAY 24 0.8107 1 1 G56 G1_TO_S_CELL_CYCLE_REACTOME 48 1 1 1 G57 G1PATHWAY 21 0.9881 1 1 G58 G2PATHWAY 18 0.9913 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 5 Table.htm 2/24/11 1:26 PM
G59 G_PROTEIN_SIGNALING 59 0.8659 1 1 G60 GAMMA_HEXACHLOROCYCLOHEXANE_DEGRADATION 15 0.9928 1 1 G61 GHPATHWAY 17 0.8196 1 1 G62 GLEEVECPATHWAY 17 0.7492 1 1 G63 GLUCONEOGENESIS 36 1 1 1 G64 GLUTAMATE_METABOLISM 15 0.824 1 1 G65 GLYCEROLIPID_METABOLISM 28 0.9927 1 1 G66 GLYCEROPHOSPHOLIPID_METABOLISM 27 0.6701 1 1 G67 GLYCOLYSIS 36 1 1 1 G68 GLYCOLYSIS_AND_GLUCONEOGENESIS 29 0.999 1 1 G69 GPCRDB_CLASS_A_RHODOPSIN_LIKE 71 0.997 1 1 G70 GPCRDB_OTHER 18 0.4655 1 1 G71 GPCRPATHWAY 22 0.9551 1 1 G72 GSK3PATHWAY 17 0.9915 1 1 G73 HDACPATHWAY 23 0.7666 1 1 G74 HISTIDINE_METABOLISM 16 0.9167 1 1 G75 HIVNEFPATHWAY 39 0.9787 1 1 G76 HSA00010_GLYCOLYSIS_AND_GLUCONEOGENESIS 38 1 1 1 G77 HSA00020_CITRATE_CYCLE 17 1 1 1 G78 HSA00051_FRUCTOSE_AND_MANNOSE_METABOLISM 19 0.7681 1 1 G79 HSA00052_GALACTOSE_METABOLISM 17 0.9822 1 1 G80 HSA00071_FATTY_ACID_METABOLISM 30 0.9996 1 1 G81 HSA00120_BILE_ACID_BIOSYNTHESIS 23 0.9977 1 1 G82 HSA00150_ANDROGEN_AND_ESTROGEN_METABOLISM 20 0.9979 1 1 G83 HSA00190_OXIDATIVE_PHOSPHORYLATION 45 1 1 1 G84 HSA00220_UREA_CYCLE_AND_METABOLISM_OF_AMINO_GROUPS 16 0.9904 1 1 G85 HSA00230_PURINE_METABOLISM 72 0.9997 1 1 G86 HSA00240_PYRIMIDINE_METABOLISM 36 0.9997 1 1 G87 HSA00251_GLUTAMATE_METABOLISM 18 0.9187 1 1 G88 HSA00252_ALANINE_AND_ASPARTATE_METABOLISM 19 0.9433 1 1 G89 HSA00280_VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 34 0.9996 1 1 G90 HSA00310_LYSINE_DEGRADATION 25 0.9451 1 1 G91 HSA00330_ARGININE_AND_PROLINE_METABOLISM 17 0.9765 1 1 G92 HSA00340_HISTIDINE_METABOLISM 21 0.9658 1 1 G93 HSA00350_TYROSINE_METABOLISM 30 1 1 1 G94 HSA00380_TRYPTOPHAN_METABOLISM 34 0.9778 1 1 G95 HSA00410_BETA_ALANINE_METABOLISM 17 0.9942 1 1 G96 HSA00500_STARCH_AND_SUCROSE_METABOLISM 38 0.9976 1 1 G97 HSA00510_N_GLYCAN_BIOSYNTHESIS 16 0.5113 1 1 G98 HSA00561_GLYCEROLIPID_METABOLISM 30 0.9769 1 1 G99 HSA00562_INOSITOL_PHOSPHATE_METABOLISM 30 0.8696 1 1 G100 HSA00564_GLYCEROPHOSPHOLIPID_METABOLISM 25 0.7683 1 1 G101 HSA00590_ARACHIDONIC_ACID_METABOLISM 24 0.9622 1 1 G102 HSA00620_PYRUVATE_METABOLISM 29 0.9894 1 1 G103 HSA00640_PROPANOATE_METABOLISM 24 0.9684 1 1 G104 HSA00650_BUTANOATE_METABOLISM 27 0.9998 1 1 G105 HSA00790_FOLATE_BIOSYNTHESIS 20 0.9867 1 1 G106 HSA00860_PORPHYRIN_AND_CHLOROPHYLL_METABOLISM 16 0.9023 1 1 G107 HSA00903_LIMONENE_AND_PINENE_DEGRADATION 16 0.9951 1 1 G108 HSA00980_METABOLISM_OF_XENOBIOTICS_BY_CYTOCHROME_P4529 0.9999 1 1 G109 HSA01030_GLYCAN_STRUCTURES_BIOSYNTHESIS_1 34 0.7493 1 1 G110 HSA01031_GLYCAN_STRUCTURES_BIOSYNTHESIS_2 29 0.9976 1 1 G111 HSA01430_CELL_COMMUNICATION 62 0.654 1 1 G112 HSA01510_NEURODEGENERATIVE_DISEASES 30 0.4564 1 1 G113 HSA02010_ABC_TRANSPORTERS_GENERAL 27 0.4318 1 1 G114 HSA03010_RIBOSOME 25 1 1 1 G115 HSA03320_PPAR_SIGNALING_PATHWAY 36 0.895 1 1 G116 HSA04012_ERBB_SIGNALING_PATHWAY 60 0.3099 1 1 G117 HSA04110_CELL_CYCLE 75 1 1 1 G118 HSA04115_P53_SIGNALING_PATHWAY 39 1 1 1 G119 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS 21 0.9595 1 1 G120 HSA04130_SNARE_INTERACTIONS_IN_VESICULAR_TRANSPORT 18 0.2926 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 5 Table.htm 2/24/11 1:26 PM
G121 HSA04150_MTOR_SIGNALING_PATHWAY 25 0.9695 1 1 G122 HSA04210_APOPTOSIS 50 0.9984 1 1 G123 HSA04310_WNT_SIGNALING_PATHWAY 79 0.9579 1 1 G124 HSA04320_DORSO_VENTRAL_AXIS_FORMATION 16 0.3245 1 1 G125 HSA04330_NOTCH_SIGNALING_PATHWAY 21 0.7012 1 1 G126 HSA04340_HEDGEHOG_SIGNALING_PATHWAY 24 0.8215 1 1 G127 HSA04350_TGF_BETA_SIGNALING_PATHWAY 60 0.9803 1 1 G128 HSA04360_AXON_GUIDANCE 68 0.4091 1 1 G129 HSA04370_VEGF_SIGNALING_PATHWAY 37 0.8572 1 1 G130 HSA04512_ECM_RECEPTOR_INTERACTION 56 0.6312 1 1 G131 HSA04514_CELL_ADHESION_MOLECULES 67 0.591 1 1 G132 HSA04520_ADHERENS_JUNCTION 57 0.9582 1 1 G133 HSA04530_TIGHT_JUNCTION 73 0.8303 1 1 G134 HSA04610_COMPLEMENT_AND_COAGULATION_CASCADES 36 0.7006 1 1 G135 HSA04612_ANTIGEN_PROCESSING_AND_PRESENTATION 32 0.6172 1 1 G136 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY 60 0.9957 1 1 G137 HSA04630_JAK_STAT_SIGNALING_PATHWAY 76 0.9843 1 1 G138 HSA04640_HEMATOPOIETIC_CELL_LINEAGE 46 0.6771 1 1 G139 HSA04650_NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY 67 0.9098 1 1 G140 HSA04660_T_CELL_RECEPTOR_SIGNALING_PATHWAY 58 0.6423 1 1 G141 HSA04662_B_CELL_RECEPTOR_SIGNALING_PATHWAY 36 0.2357 1 1 G142 HSA04664_FC_EPSILON_RI_SIGNALING_PATHWAY 41 0.5396 1 1 G143 HSA04670_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION 62 0.9687 1 1 G144 HSA04740_OLFACTORY_TRANSDUCTION 16 0.4813 1 1 G145 HSA04742_TASTE_TRANSDUCTION 15 0.569 1 1 G146 HSA04910_INSULIN_SIGNALING_PATHWAY 80 1 1 1 G147 HSA04912_GNRH_SIGNALING_PATHWAY 57 0.1246 1 1 G148 HSA04916_MELANOGENESIS 53 0.8599 1 1 G149 HSA04920_ADIPOCYTOKINE_SIGNALING_PATHWAY 44 0.5849 1 1 G150 HSA04930_TYPE_II_DIABETES_MELLITUS 27 0.9972 1 1 G151 HSA04940_TYPE_I_DIABETES_MELLITUS 28 0.3862 1 1 G152 HSA05040_HUNTINGTONS_DISEASE 22 0.621 1 1 G153 HSA05050_DENTATORUBROPALLIDOLUYSIAN_ATROPHY 15 0.6773 1 1 G154 HSA05110_CHOLERA_INFECTION 26 0.8243 1 1 G155 HSA05120_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI46 0.9995 1 1 G156 HSA05130_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EHEC 19 0.8199 1 1 G157 HSA05131_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EPEC 19 0.8199 1 1 G158 HSA05210_COLORECTAL_CANCER 53 0.9978 1 1 G159 HSA05211_RENAL_CELL_CARCINOMA 42 0.8788 1 1 G160 HSA05212_PANCREATIC_CANCER 55 0.9978 1 1 G161 HSA05213_ENDOMETRIAL_CANCER 33 0.976 1 1 G162 HSA05214_GLIOMA 46 0.9092 1 1 G163 HSA05215_PROSTATE_CANCER 62 0.9998 1 1 G164 HSA05216_THYROID_CANCER 18 0.892 1 1 G165 HSA05217_BASAL_CELL_CARCINOMA 23 0.9975 1 1 G166 HSA05218_MELANOMA 46 0.9895 1 1 G167 HSA05219_BLADDER_CANCER 29 0.8157 1 1 G168 HSA05220_CHRONIC_MYELOID_LEUKEMIA 56 0.9991 1 1 G169 HSA05221_ACUTE_MYELOID_LEUKEMIA 36 0.9906 1 1 G170 HSA05222_SMALL_CELL_LUNG_CANCER 61 0.9878 1 1 G171 HSA05223_NON_SMALL_CELL_LUNG_CANCER 37 0.7814 1 1 G172 IL1RPATHWAY 22 0.9853 1 1 G173 IL2RBPATHWAY 24 0.8147 1 1 G174 INOSITOL_PHOSPHATE_METABOLISM 17 0.4886 1 1 G175 INTEGRIN_MEDIATED_CELL_ADHESION_KEGG 63 0.8451 1 1 G176 INTEGRINPATHWAY 22 0.3482 1 1 G177 KERATINOCYTEPATHWAY 33 0.8874 1 1 G178 KREBS_TCA_CYCLE 17 0.9968 1 1 G179 LYSINE_DEGRADATION 20 0.773 1 1 G180 MAPKPATHWAY 59 0.9812 1 1 G181 MCALPAINPATHWAY 15 0.938 1 1 G182 METPATHWAY 27 0.8766 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 5 Table.htm 2/24/11 1:26 PM
G183 MRNA_PROCESSING_REACTOME 62 1 1 1 G184 MTORPATHWAY 18 0.992 1 1 G185 NFATPATHWAY 33 0.9707 1 1 G186 NFKBPATHWAY 17 0.8554 1 1 G187 NKTPATHWAY 17 0.8544 1 1 G188 NO1PATHWAY 20 0.9748 1 1 G189 NOS1PATHWAY 16 0.7534 1 1 G190 NTHIPATHWAY 18 0.8909 1 1 G191 NUCLEAR_RECEPTORS 26 0.7139 1 1 G192 OVARIAN_INFERTILITY_GENES 19 0.9436 1 1 G193 OXIDATIVE_PHOSPHORYLATION 28 0.9997 1 1 G194 P38MAPKPATHWAY 25 0.8293 1 1 G195 PAR1PATHWAY 16 0.8923 1 1 G196 PDGFPATHWAY 18 0.4852 1 1 G197 PEPTIDE_GPCRS 35 0.7641 1 1 G198 PGC1APATHWAY 16 0.2228 1 1 G199 PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 61 0.8374 1 1 G200 PHOTOSYNTHESIS 15 0.9956 1 1 G201 PPARAPATHWAY 30 0.5466 1 1 G202 PROPANOATE_METABOLISM 24 0.9841 1 1 G203 PROSTAGLANDIN_AND_LEUKOTRIENE_METABOLISM 15 0.6807 1 1 G204 PROSTAGLANDIN_SYNTHESIS_REGULATION 16 0.8396 1 1 G205 PTDINSPATHWAY 15 0.5331 1 1 G206 PURINE_METABOLISM 59 0.996 1 1 G207 PYK2PATHWAY 20 0.8922 1 1 G208 PYRIMIDINE_METABOLISM 27 0.9958 1 1 G209 PYRUVATE_METABOLISM 28 0.9978 1 1 G210 RAC1PATHWAY 18 0.4389 1 1 G211 RACCYCDPATHWAY 19 0.909 1 1 G212 RHOPATHWAY 18 0.5048 1 1 G213 RIBOSOMAL_PROTEINS 33 0.9951 1 1 G214 RNA_TRANSCRIPTION_REACTOME 17 0.9842 1 1 G215 SIG_CD40PATHWAYMAP 23 0.9936 1 1 G216 SIG_IL4RECEPTOR_IN_B_LYPHOCYTES 20 0.9695 1 1 G217 SIG_INSULIN_RECEPTOR_PATHWAY_IN_CARDIAC_MYOCYTES 33 0.4636 1 1 G218 SIG_PIP3_SIGNALING_IN_CARDIAC_MYOCTES 43 0.3661 1 1 G219 SIG_REGULATION_OF_THE_ACTIN_CYTOSKELETON_BY_RHO_GTPASES24 0.8659 1 1 G220 SMOOTH_MUSCLE_CONTRACTION 82 0.3352 1 1 G221 SPPAPATHWAY 16 0.9135 1 1 G222 ST_B_CELL_ANTIGEN_RECEPTOR 29 0.7438 1 1 G223 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS 27 0.6696 1 1 G224 ST_ERK1_ERK2_MAPK_PATHWAY 15 0.2851 1 1 G225 ST_FAS_SIGNALING_PATHWAY 36 1 1 1 G226 ST_GA12_PATHWAY 16 0.4583 1 1 G227 ST_GA13_PATHWAY 28 0.9999 1 1 G228 ST_INTEGRIN_SIGNALING_PATHWAY 58 0.984 1 1 G229 ST_INTERLEUKIN_4_PATHWAY 18 0.8888 1 1 G230 ST_JNK_MAPK_PATHWAY 30 0.6518 1 1 G231 ST_P38_MAPK_PATHWAY 21 0.8223 1 1 G232 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY 23 0.6306 1 1 G233 ST_T_CELL_SIGNAL_TRANSDUCTION 30 0.8349 1 1 G234 ST_TUMOR_NECROSIS_FACTOR_PATHWAY 20 0.9958 1 1 G235 ST_WNT_BETA_CATENIN_PATHWAY 18 0.8566 1 1 G236 STARCH_AND_SUCROSE_METABOLISM 20 0.9896 1 1 G237 STRESSPATHWAY 18 0.9884 1 1 G238 STRIATED_MUSCLE_CONTRACTION 23 0.9211 1 1 G239 TCRPATHWAY 30 0.4264 1 1 G240 TIDPATHWAY 15 0.9766 1 1 G241 TNFR1PATHWAY 20 0.9853 1 1 G242 TNFR2PATHWAY 15 0.7946 1 1 G243 TOLLPATHWAY 21 0.5792 1 1 G244 TPOPATHWAY 16 0.3718 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 5 Table.htm 2/24/11 1:26 PM
G245 TRANSLATION_FACTORS 23 1 1 1 G246 TRYPTOPHAN_METABOLISM 34 0.9944 1 1 G247 TYROSINE_METABOLISM 20 0.9996 1 1 G248 VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION 28 0.9893 1 1 G249 VEGFPATHWAY 17 0.9913 1 1 G250 VIPPATHWAY 20 0.981 1 1 G251 WNT_SIGNALING 35 0.88 1 1 G252 WNTPATHWAY 17 0.9764 1 1
Note: Software GSAA-SNP (version 1.0) won't report gene sets with a negative AS score because negative scores are not biologically meaningful in GSAA-SNP.
file:///Users/sayan/Desktop/Qing/Table.htm Page 5 of 5 Table S13b ClickTable.htm here to download Table: Table S13b.pdf 2/24/11 1:31 PM
Table S13b. Canonical pathways associated with case or control samples in GSAA-SNP (CD) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 ST_GAQ_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_GAQ_PATHWAY.html G2 deprecated http://stke.sciencemag.org/cgi/cm/stkecm;CMP_7918 G3 KEGG_GLYCINE_SERINE_AND_THREONINE_METABOLISM http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GLYCINE_SERINE_AND_THREONINE_METABOLISM.html G4 ST_WNT_CA2_CYCLIC_GMP_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_WNT_CA2_CYCLIC_GMP_PATHWAY.html G5 SA_B_CELL_RECEPTOR_COMPLEXES http://www.broadinstitute.org/gsea/msigdb/cards/SA_B_CELL_RECEPTOR_COMPLEXES.html G6 SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES http://www.broadinstitute.org/gsea/msigdb/cards/SIG_PIP3_SIGNALING_IN_B_LYMPHOCYTES.html G7 ST_MYOCYTE_AD_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/ST_MYOCYTE_AD_PATHWAY.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S13c ClickTable.htm here to download Table: Table S13c.pdf 2/24/11 1:34 PM
Table S13. Canonical pathways associated with case or control samples in GSAA-SNP (CD) Sorted by FDR Index Description G1 G-alpha-q activates phospholipase C, resulting in calcium influx and increasing protein kinase C activity. G2 The fungus Dictyostelium discoideum is a model system for cytoskeletal organization during chemotaxis. G3 Genes involved in glycine, serine and threonine metabolism G4 Some Wnt glycoprotein/Frizzled receptor interactions increase intracellular calcium and decrease cGMP. G5 Antigen binding to B cell receptors activates protein tyrosine kinases, such as the Src family, which ultimate activate MAP kinases. G6 Genes related to PIP3 signaling in B lymphocytes G7 Cardiac myocytes have a variety of adrenergic receptors that induce subtype-specific signaling effects.
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S13d Click here to download Table: Table S13d.pdf
Table S13d. Canonical pathways associated with case or control samples in GSAA-SNP (CD)
Sorted by FDR
Index Genes
G1 ADRBK1 AKT1 AKT2 AKT3 BF DAG1 GNAQ IKBKG ITPKA ITPKB ITPR1 ITPR2 ITPR3 NFKB1 NFKB2 NFKBIA NFKBIB NFKBIE NFKBIL1 NFKBIL2 PDK1 PHKA2 PIK3CB PITX2 PLD1 PLD2 PLD3 VN1R1
G2 ACTR2 ACTR3 AKT1 ANGPTL2 BF DAG1 DGKA ETFA GCA ITGA9 ITPKA ITPKB ITPR1 ITPR2 ITPR3 MAP2K1 MAPK1 MAPK3 NR1I3 PAK1 PDE3A PDE3B PI3 PIK3C2G PIK3CA PIK3CD PIK3R1 PLDN PSME1 RIPK3 RPS4X SGCB VASP G3 ABP1 AGXT AGXT2 AKR1B10 ALAS1 ALAS2 AMT AOC2 AOC3 BHMT CBS CHDH CHKA CHKB CTH DAO DLD DMGDH GAMT GARS GATM GCAT GLDC GNMT HSD3B7 MAOA MAOB PEMT PHGDH PIPOX PISD PSAT1 PSPH RDH11 RDH12 RDH13 RDH14 SARDH SARS SARS2 SDS SHMT1 SHMT2 TARS TARS2 G4 BF CAMK2A CAMK2B CAMK2D CAMK2G DAG1 ITPKA ITPKB ITPR1 ITPR2 ITPR3 NFAT5 PDE6A PDE6B PDE6C PDE6D PDE6G PDE6H SLC6A13 TF
G5 ATF2 BCR BLNK ELK1 FOS GRB2 HRAS JUN LYN MAP2K1 MAP3K1 MAPK1 MAPK3 MAPK8IP3 PAPPA RAC1 RPS6KA1 RPS6KA3 SHC1 SOS1 SYK VAV1 VAV2 VAV3
G6 AKT1 AKT2 AKT3 BCR BTK CD19 CDKN2A DAPP1 FLOT1 FLOT2 FOXO3A GAB1 ITPR1 ITPR2 ITPR3 LYN NR0B2 P101-PI3K PDK1 PHF11 PIK3CA PITX2 PLCG2 PPP1R13B PREX1 PSCD3 PTEN PTPRC RPS6KA1 RPS6KA2 RPS6KA3 RPS6KB1 SAG SYK TEC VAV1 G7 ADRB1 AKT1 APC ASAH1 BF CAMP CAV3 DAG1 DLG4 EPHB2 GAS GNAI1 GNAQ HTATIP ITPR1 ITPR2 ITPR3 KCNJ3 KCNJ5 KCNJ9 MAPK1 PITX2 PLB PTX1 PTX3 RAC1 RHO RYR1 Table S14a ClickTable here S14.htm to download Table: Table S14a.pdf 2/24/11 1:14 PM
Table S14a. Canonical pathways associated with case samples in GSEAndes (CD) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 PROTEASOME 15 0.041300192 0.18541968 0.4318 G2 PROTEASOMEPATHWAY 21 0.009908685 0.22534715 0.4048 G3 HSA03050_PROTEASOME 22 0.108155005 0.23657845 0.7975 G4 SA_MMP_CYTOKINE_CONNECTION 15 0.024696356 0.24525568 0.7812 G5 ST_TUMOR_NECROSIS_FACTOR_PATHWAY 27 0.034537517 0.25054693 0.8911 G6 IL1RPATHWAY 28 0.001223491 0.2533356 0.9128 G7 IL6PATHWAY 21 0.018928716 0.2646677 0.9107 G8 ERYTHPATHWAY 15 0.01585688 0.26583987 0.8895 G9 AMINOACYL_TRNA_BIOSYNTHESIS 17 0.017220665 0.2702151 0.7764 G10 TNFR2PATHWAY 18 0.036556605 0.2753986 0.8528 G11 NFKBPATHWAY 22 0.01785364 0.27760577 0.8687 G12 NTHIPATHWAY 21 0.005532787 0.27879223 0.8841 G13 HSA00970_AMINOACYL_TRNA_BIOSYNTHESIS 19 0.015072348 0.29029918 0.7624 G14 STEMPATHWAY 15 0.003861789 0.3020292 0.9578 G15 CALCINEURIN_NF_AT_SIGNALING 89 0.00868336 0.3100612 0.956 G16 HSA04940_TYPE_I_DIABETES_MELLITUS 36 0.025984572 0.31131476 0.9463 G17 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY 87 0.008355411 0.31646597 0.9531 G18 HSA03030_DNA_POLYMERASE 16 0.033699892 0.32029715 0.3894 G19 APOPTOSIS_KEGG 46 0.06742717 0.32676256 0.9677 G20 HSA00052_GALACTOSE_METABOLISM 24 0.01512605 0.3285842 0.983 G21 HSA05120_EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTION 56 0.007 0.32907185 0.9751 G22 HSA05219_BLADDER_CANCER 41 0 0.32921508 0.7555 G23 ATRBRCAPATHWAY 17 0.07506437 0.33087483 0.9846 G24 CCR5PATHWAY 16 0.054769967 0.33588552 0.9803 G25 RELAPATHWAY 16 0.31164137 0.3382698 0.9825 G26 ST_T_CELL_SIGNAL_TRANSDUCTION 39 0.05528134 0.33887452 0.9749 G27 INFLAMPATHWAY 28 0.040943928 0.3459688 0.9803 G28 ST_FAS_SIGNALING_PATHWAY 52 0.011665326 0.34734312 0.9742 G29 LAIRPATHWAY 15 0.025855212 0.37068912 0.9894 G30 ST_B_CELL_ANTIGEN_RECEPTOR 38 0.053692658 0.37852392 0.9911 G31 EICOSANOID_SYNTHESIS 15 0.0058 0.3843271 0.7474 G32 CIRCADIAN_EXERCISE 39 0.026701465 0.38768625 0.9928 G33 IL3PATHWAY 15 0.14059098 0.39411366 0.2599 G34 HSA04612_ANTIGEN_PROCESSING_AND_PRESENTATION 57 0.061408915 0.52456677 0.9981 G35 G1PATHWAY 25 0.15907305 0.5337016 0.9984 G36 GALACTOSE_METABOLISM 21 0.1031175 0.55626297 0.999 G37 PYRIMIDINE_METABOLISM 45 0.063918754 0.55848086 0.9988 G38 BREAST_CANCER_ESTROGEN_SIGNALING 89 0.010610079 0.5691148 0.999 G39 TOLLPATHWAY 27 0.07944767 0.58152276 0.9992 G40 HSA04920_ADIPOCYTOKINE_SIGNALING_PATHWAY 62 0.03551198 0.5932019 0.9992 G41 HSA04514_CELL_ADHESION_MOLECULES 97 0.12250252 0.6755356 0.9997 G42 PROSTAGLANDIN_SYNTHESIS_REGULATION 24 0.053582426 0.68239665 0.9996 G43 NO2IL12PATHWAY 15 0.22968408 0.68905586 0.9997 G44 HSA00240_PYRIMIDINE_METABOLISM 57 0.13079074 0.69107604 0.9997 G45 NKTPATHWAY 26 0.15029252 0.6985675 0.9996 G46 CYTOKINEPATHWAY 20 0.11875127 0.69986254 0.9995 G47 APOPTOSIS_GENMAPP 41 0.18620546 0.7016501 0.9997 G48 HSA04640_HEMATOPOIETIC_CELL_LINEAGE 82 0.11790924 0.7047831 0.9998 G49 UBIQUITIN_MEDIATED_PROTEOLYSIS 20 0.34330985 0.7070111 0.9999 G50 PPARAPATHWAY 49 0.2024681 0.70874876 0.9999 G51 HSA04610_COMPLEMENT_AND_COAGULATION_CASCADES 61 0.13478434 0.71099985 0.9999 G52 FMLPPATHWAY 33 0.29577196 0.71279675 0.9999 G53 GHPATHWAY 27 0.32749492 0.7133395 0.9999 G54 HSA05215_PROSTATE_CANCER 80 0.24282786 0.71365976 0.9999 G55 HSA05040_HUNTINGTONS_DISEASE 24 0.2970625 0.71527755 0.9999 G56 CASPASEPATHWAY 21 0.2972155 0.7164565 0.9999
file:///Users/sayan/Desktop/Qing/Table%20S14.htm Page 1 of 4 Table S14.htm 2/24/11 1:14 PM
G57 TELPATHWAY 15 0.39996174 0.71744007 0.9998 G58 ST_DICTYOSTELIUM_DISCOIDEUM_CAMP_CHEMOTAXIS_PATHWAY 29 0.3024 0.71843946 0.9999 G59 FASPATHWAY 26 0.37268934 0.7188046 1 G60 HSA04370_VEGF_SIGNALING_PATHWAY 58 0.22150101 0.71920174 0.9999 G61 RACCYCDPATHWAY 22 0.41067845 0.71998686 0.9999 G62 HSA00590_ARACHIDONIC_ACID_METABOLISM 37 0.36047047 0.722966 1 G63 INSULINPATHWAY 21 0.43245435 0.7238998 1 G64 HSA04660_T_CELL_RECEPTOR_SIGNALING_PATHWAY 84 0.20788744 0.7248088 0.9999 G65 ACTINYPATHWAY 16 0.3058564 0.72566456 0.9999 G66 DNA_REPLICATION_REACTOME 39 0.3888889 0.7257595 1 G67 HSA04210_APOPTOSIS 75 0.34477222 0.7259429 1 G68 PURINE_METABOLISM 97 0.13442037 0.72620434 0.9999 G69 CHOLESTEROL_BIOSYNTHESIS 15 0.4496948 0.7265859 1 G70 TRANSLATION_FACTORS 39 0.41469195 0.7271754 1 G71 HSA05131_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EPEC 33 0.20003934 0.72825086 0.9998 G72 STRESSPATHWAY 24 0.33988485 0.7283701 0.9999 G73 HSA00380_TRYPTOPHAN_METABOLISM 42 0.13306288 0.72890735 0.9998 G74 ST_G_ALPHA_I_PATHWAY 33 0.28393325 0.73021156 0.9999 G75 HYPERTROPHY_MODEL 17 0.36927623 0.7310047 1 G76 HSA04130_SNARE_INTERACTIONS_IN_VESICULAR_TRANSPORT 26 0.30567598 0.73126525 0.9999 G77 P53PATHWAY 15 0.32945353 0.7332751 0.9999 G78 TYPE_III_SECRETION_SYSTEM 17 0.51662797 0.73358166 1 G79 PDGFPATHWAY 27 0.28192535 0.7340535 0.9999 G80 ARAPPATHWAY 17 0.40438324 0.7351979 0.9999 G81 HIVNEFPATHWAY 51 0.403437 0.73524326 1 G82 PROSTAGLANDIN_AND_LEUKOTRIENE_METABOLISM 26 0.16100064 0.7353889 0.9999 G83 SIG_IL4RECEPTOR_IN_B_LYPHOCYTES 26 0.40679026 0.73585033 1 G84 MAPKPATHWAY 79 0.33625498 0.73648554 1 G85 HSA04110_CELL_CYCLE 98 0.39730707 0.73709863 1 G86 GSK3PATHWAY 23 0.38778353 0.7372346 1 G87 HSA00252_ALANINE_AND_ASPARTATE_METABOLISM 23 0.426492 0.73731077 1 G88 KERATINOCYTEPATHWAY 42 0.24708484 0.7374325 0.9999 G89 APOPTOSIS 63 0.21020283 0.7379741 0.9998 G90 HSA00051_FRUCTOSE_AND_MANNOSE_METABOLISM 29 0.23010567 0.73919153 0.9999 G91 FLAGELLAR_ASSEMBLY 17 0.51662797 0.7406354 1 G92 HSA05212_PANCREATIC_CANCER 70 0.17296974 0.7406506 0.9999 G93 HSA05130_PATHOGENIC_ESCHERICHIA_COLI_INFECTION_EHEC 33 0.20003934 0.74225575 0.9998 G94 HSA00530_AMINOSUGARS_METABOLISM 17 0.30593517 0.74251497 0.9999 G95 TIDPATHWAY 17 0.4464114 0.74312615 1 G96 TRYPTOPHAN_METABOLISM 47 0.41757536 0.74316835 1 G97 41BBPATHWAY 18 0.38166732 0.74493015 1 G98 ST_ERK1_ERK2_MAPK_PATHWAY 25 0.3659027 0.74512666 1 G99 HSA04670_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION 89 0.13533534 0.74550575 0.9999 G100 HSA00510_N_GLYCAN_BIOSYNTHESIS 24 0.39233685 0.74715865 1 G101 ST_GA13_PATHWAY 35 0.33594063 0.7477839 1 G102 ATP_SYNTHESIS 17 0.51662797 0.74782604 1 G103 HSA00100_BIOSYNTHESIS_OF_STEROIDS 21 0.32164785 0.75142497 0.9999 G104 EPOPATHWAY 19 0.5310871 0.7532219 1 G105 TNFR1PATHWAY 27 0.36256018 0.7547192 1 G106 HSA05222_SMALL_CELL_LUNG_CANCER 83 0.26343542 0.75644207 1 G107 ST_INTERLEUKIN_4_PATHWAY 24 0.24403341 0.75841856 0.9999 G108 HSA04664_FC_EPSILON_RI_SIGNALING_PATHWAY 64 0.29588765 0.75876725 1 G109 PHOTOSYNTHESIS 18 0.53385216 0.75880295 1 G110 HSA05220_CHRONIC_MYELOID_LEUKEMIA 71 0.43732423 0.76257145 1 G111 TPOPATHWAY 23 0.23718199 0.765912 0.9999 G112 CARBON_FIXATION 18 0.48148924 0.76796716 1 G113 CSKPATHWAY 21 0.5788311 0.77060544 1 G114 CDMACPATHWAY 15 0.6336799 0.7713483 1 G115 VEGFPATHWAY 26 0.4668576 0.7716024 1
file:///Users/sayan/Desktop/Qing/Table%20S14.htm Page 2 of 4 Table S14.htm 2/24/11 1:14 PM
G116 PHOSPHATIDYLINOSITOL_SIGNALING_SYSTEM 83 0.59282404 0.77223265 1 G117 AMIPATHWAY 21 0.5788311 0.7762716 1 G118 IGF1RPATHWAY 15 0.5111386 0.7769836 1 G119 GPCRDB_OTHER 34 0.46762154 0.7772135 1 G120 BLOOD_CLOTTING_CASCADE 19 0.5404653 0.7786655 1 G121 IGF1PATHWAY 20 0.52651745 0.7806757 1 G122 HSA00330_ARGININE_AND_PROLINE_METABOLISM 26 0.5012963 0.7812647 1 G123 P38MAPKPATHWAY 39 0.57088584 0.7815802 1 G124 TH1TH2PATHWAY 16 0.6171767 0.78256696 1 G125 MITOCHONDRIAPATHWAY 18 0.5382244 0.7830989 1 G126 HSA04512_ECM_RECEPTOR_INTERACTION 73 0.5017843 0.7849216 1 G127 HSA00565_ETHER_LIPID_METABOLISM 19 0.5417987 0.7852976 1 G128 INTRINSICPATHWAY 22 0.625171 0.7855785 1 G129 IL2RBPATHWAY 34 0.56976044 0.78573954 1 G130 HSA04115_P53_SIGNALING_PATHWAY 52 0.5019266 0.7874409 1 G131 ARGININE_AND_PROLINE_METABOLISM 38 0.52247036 0.7886783 1 G132 DEATHPATHWAY 31 0.5424646 0.7889795 1 G133 CK1PATHWAY 16 0.55766225 0.7898108 1 G134 HSA05221_ACUTE_MYELOID_LEUKEMIA 50 0.5688219 0.7901008 1 G135 WNT_SIGNALING 49 0.55544555 0.79026103 1 G136 CELL_CYCLE_KEGG 76 0.56542814 0.79442126 1 G137 SPPAPATHWAY 21 0.55048466 0.79487836 1 G138 FCER1PATHWAY 36 0.5843325 0.8007166 1 G139 SA_B_CELL_RECEPTOR_COMPLEXES 23 0.56198347 0.8017805 1 G140 MRNA_PROCESSING_REACTOME 96 0.55978924 0.80309397 1 G141 FRUCTOSE_AND_MANNOSE_METABOLISM 21 0.658066 0.80729926 1 G142 HSA01430_CELL_COMMUNICATION 93 0.6625481 0.81561446 1 G143 AKTPATHWAY 17 0.6429716 0.85332006 1 G144 N_GLYCAN_BIOSYNTHESIS 17 0.66451615 0.8585298 1 G145 CARM_ERPATHWAY 24 0.6309804 0.85916984 1 G146 HSA00790_FOLATE_BIOSYNTHESIS 27 0.7013376 0.8647645 1 G147 G2PATHWAY 22 0.6672 0.87200826 1 G148 HSA04330_NOTCH_SIGNALING_PATHWAY 32 0.6986987 0.8735429 1 G149 VIPPATHWAY 25 0.74341327 0.8891027 1 G150 HSA01510_NEURODEGENERATIVE_DISEASES 35 0.7610088 0.8926353 1 G151 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS 41 0.71860605 0.89425564 1 G152 CELLCYCLEPATHWAY 23 0.70917046 0.8969394 1 G153 GCRPATHWAY 16 0.72410953 0.8981518 1 G154 EIF4PATHWAY 23 0.7247225 0.9022494 1 G155 EDG1PATHWAY 24 0.7084739 0.9078073 1 G156 WNTPATHWAY 23 0.719 0.9089264 1 G157 PENTOSE_PHOSPHATE_PATHWAY 19 0.73891306 0.9102544 1 G158 ETSPATHWAY 16 0.7587949 0.91256183 1 G159 CHEMICALPATHWAY 20 0.7610114 0.91832167 1 G160 INOSITOL_PHOSPHATE_METABOLISM 22 0.76357377 0.918637 1 G161 IL7PATHWAY 16 0.8118096 0.9368881 1 G162 HSA05050_DENTATORUBROPALLIDOLUYSIAN_ATROPHY 15 0.78172886 0.93856114 1 G163 HSA01032_GLYCAN_STRUCTURES_DEGRADATION 21 0.8047739 0.94396883 1 G164 ST_INTEGRIN_SIGNALING_PATHWAY 72 0.8642303 0.9473024 1 G165 HSA00030_PENTOSE_PHOSPHATE_PATHWAY 21 0.8800994 0.9479628 1 G166 UCALPAINPATHWAY 16 0.8214696 0.94868124 1 G167 ST_P38_MAPK_PATHWAY 32 0.934881 0.9499902 1 G168 IL12PATHWAY 20 0.89767253 0.95020604 1 G169 ATMPATHWAY 17 0.8596173 0.9523381 1 G170 SIG_BCR_SIGNALING_PATHWAY 43 0.9182111 0.952557 1 G171 HSA05110_CHOLERA_INFECTION 33 0.90332514 0.95477605 1 G172 HSA01030_GLYCAN_STRUCTURES_BIOSYNTHESIS_1 52 0.9587442 0.95507693 1 G173 CXCR4PATHWAY 23 0.85001004 0.95517826 1 G174 G1_TO_S_CELL_CYCLE_REACTOME 62 0.93895113 0.95653677 1
file:///Users/sayan/Desktop/Qing/Table%20S14.htm Page 3 of 4 Table S14.htm 2/24/11 1:14 PM
G175 HSA00710_CARBON_FIXATION 19 0.8671063 0.95708305 1 G176 NDKDYNAMINPATHWAY 15 0.8199692 0.95792633 1 G177 HSA05010_ALZHEIMERS_DISEASE 19 0.8792091 0.9590657 1 G178 INTEGRIN_MEDIATED_CELL_ADHESION_KEGG 78 0.9713998 0.9805298 1 G179 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS 27 0.9788987 0.98722464 1 G180 HSP27PATHWAY 15 0.88509494 0.9902558 1 G181 HSA03022_BASAL_TRANSCRIPTION_FACTORS 25 0.9901902 0.99154896 1 G182 RNA_TRANSCRIPTION_REACTOME 29 0.92947304 0.9926946 1 G183 INTEGRINPATHWAY 33 0.98486686 0.9942287 1 G184 CCR3PATHWAY 22 0.96176356 0.9961973 1 G185 HSA03010_RIBOSOME 54 1 1 1 G186 MONOAMINE_GPCRS 22 1 1 1 G187 RIBOSOMAL_PROTEINS 77 1 1 1
file:///Users/sayan/Desktop/Qing/Table%20S14.htm Page 4 of 4 Table S14b ClickTable.htm here to download Table: Table S14b.pdf 2/24/11 1:17 PM
Table S14b. Canonical pathways associated with case samples in GSEAndes (CD) Sorted by FDR Index Gene Set Name in MSigDB v3.0 Database Links G1 KEGG_PROTEASOME http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PROTEASOME.html G2 BIOCARTA_PROTEASOME_PATHWAY http://www.broadinstitute.org/gsea/msigdb/cards/BIOCARTA_PROTEASOME_PATHWAY.html G3 KEGG_PROTEASOME http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_PROTEASOME.html G4 SA_MMP_CYTOKINE_CONNECTION http://www.broadinstitute.org/gsea/msigdb/cards/SA_MMP_CYTOKINE_CONNECTION.html
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S14c ClickTable.htm here to download Table: Table S14c.pdf 2/24/11 1:18 PM
Table S14c. Canonical pathways associated with case samples in GSEAndes (CD) Sorted by FDR Index Description G1 G2 Ubiquitinated proteins are targeted for proteolytic degradation by the proteasome, where they are unfolded and degraded to small peptides in an ATP-dependent process. G3 Genes involved in proteasome G4 Cytokines can induce activation of matrix metalloproteinases, which degrade extracellular matrix.
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 1 Table S14d Click here to download Table: Table S14d.pdf
Table S14d. Canonical pathways associated with case samples in GSEAndes (CD)
Sorted by FDR
Index Genes
G1 PSMA1 PSMA2 PSMA3 PSMA4 PSMA5 PSMA6 PSMA7 PSMB1 PSMB10 PSMB2 PSMB3 PSMB4 PSMB5 PSMB6 PSMB7 PSMB8 PSMB9 G2 PSMA1 PSMA2 PSMA3 PSMA4 PSMA5 PSMA6 PSMA7 PSMB1 PSMB2 PSMB3 PSMB4 PSMB5 PSMB6 PSMB7 PSMC3 PSMD14 RPN1 RPN2 UBE1 UBE2A UBE3A G3 PSMA1 PSMA2 PSMA3 PSMA4 PSMA5 PSMA6 PSMA7 PSMB1 PSMB2 PSMB3 PSMB4 PSMB5 PSMB6 PSMB7 PSMC2 PSMC3 PSMD1 PSMD11 PSMD12 PSMD13 PSMD2 PSMD6 G4 ACE CD44 CSF1 FCGR3A IL1B IL6R SELL SPN TGFB1 TGFB2 TNF TNFRSF1A TNFRSF1B TNFRSF8 TNFSF8 Table S15 ClickTable.htm here to download Table: Table S15.pdf 2/24/11 1:12 PM
Table S15. Canonical pathways associated with control samples in GSEAndes (CD) Sorted by FDR Index Gene Set Name Size P-value FDR FWER G1 HSA05216_THYROID_CANCER 27 0.0217045 0.74254876 0.7193 G2 PYK2PATHWAY 26 0.9237105 0.9745151 1 G3 CERAMIDEPATHWAY 22 0.8635764 0.9781374 1 G4 ST_GA12_PATHWAY 20 0.8875442 0.9825376 1 G5 SPRYPATHWAY 16 0.9244119 0.9830451 1 G6 MPRPATHWAY 23 0.9732753 0.9842539 1 G7 SA_PTEN_PATHWAY 16 0.9106079 0.9880429 1 G8 HSA01031_GLYCAN_STRUCTURES_B40 0.8626267 0.99032503 1 G9 SIG_REGULATION_OF_THE_ACTIN_C31 0.8446714 0.9920426 1 G10 ST_GRANULE_CELL_SURVIVAL_PATH24 0.93024653 0.9935638 1 G11 IGF1MTORPATHWAY 19 0.7323478 0.9943505 1 G12 HSA04916_MELANOGENESIS 78 0.907422 0.9961562 1 G13 ST_PHOSPHOINOSITIDE_3_KINASE_ 31 0.9566079 0.9994542 1 G14 PTDINSPATHWAY 20 0.019292604 1 0.66 G15 HSA00071_FATTY_ACID_METABOLIS39 0.022084463 1 0.9951 G16 HSA03320_PPAR_SIGNALING_PATH 52 0.024725754 1 1 G17 HSA00260_GLYCINE_SERINE_AND_T33 0.034168955 1 0.9816 G18 HSA00650_BUTANOATE_METABOLI 32 0.05831904 1 0.9977 G19 ST_WNT_CA2_CYCLIC_GMP_PATHW18 0.059429016 1 0.9376 G20 HSA04740_OLFACTORY_TRANSDUCT25 0.059737638 1 0.9898 G21 DCPATHWAY 18 0.066785224 1 0.9937 G22 GLYCINE_SERINE_AND_THREONINE_31 0.072839506 1 0.9937 G23 HSA00310_LYSINE_DEGRADATION 30 0.075593956 1 0.9987 G24 BIOPEPTIDESPATHWAY 36 0.11518016 1 0.9994 G25 TYROSINE_METABOLISM 27 0.12079091 1 0.9992 G26 P53HYPOXIAPATHWAY 18 0.12553109 1 0.9992 G27 BUTANOATE_METABOLISM 24 0.13062438 1 0.9991 G28 HSA00120_BILE_ACID_BIOSYNTHESI 28 0.13215339 1 1 G29 HSA00280_VALINE_LEUCINE_AND_I 40 0.13603158 1 1 G30 HSA05213_ENDOMETRIAL_CANCER 46 0.13617767 1 1 G31 HSA04150_MTOR_SIGNALING_PATH39 0.13848281 1 1 G32 HSA04930_TYPE_II_DIABETES_MELLI38 0.14435798 1 1 G33 ERKPATHWAY 29 0.14740726 1 0.9992 G34 HSA00620_PYRUVATE_METABOLISM34 0.15395203 1 1 G35 HSA00220_UREA_CYCLE_AND_MET 25 0.17639448 1 1 G36 HSA04950_MATURITY_ONSET_DIAB17 0.18511264 1 1 G37 HSA00360_PHENYLALANINE_METAB22 0.19150962 1 1 G38 NITROGEN_METABOLISM 17 0.19562297 1 1 G39 HSA00600_SPHINGOLIPID_METABO 24 0.21503216 1 1 G40 RAC1PATHWAY 22 0.21768437 1 1 G41 HSA05218_MELANOMA 58 0.23458736 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 1 of 4 Table.htm 2/24/11 1:12 PM
G42 HSA00564_GLYCEROPHOSPHOLIPID 41 0.23992015 1 1 G43 CTLA4PATHWAY 16 0.24122015 1 1 G44 HSA00910_NITROGEN_METABOLIS 19 0.24204545 1 1 G45 BETA_ALANINE_METABOLISM 23 0.24208456 1 1 G46 HSA04320_DORSO_VENTRAL_AXIS_ 18 0.243888 1 1 G47 PYRUVATE_METABOLISM 33 0.25113255 1 1 G48 VALINE_LEUCINE_AND_ISOLEUCINE 33 0.2529976 1 1 G49 HSA00450_SELENOAMINO_ACID_M 15 0.26966506 1 1 G50 HSA05217_BASAL_CELL_CARCINOM 35 0.274 1 1 G51 ANDROGEN_AND_ESTROGEN_META18 0.27497086 1 1 G52 PROPANOATE_METABOLISM 27 0.27710363 1 1 G53 G_PROTEIN_SIGNALING 80 0.2838557 1 1 G54 HSA04340_HEDGEHOG_SIGNALING_39 0.29975873 1 1 G55 HSA00632_BENZOATE_DEGRADATIO15 0.30117133 1 1 G56 HSA05030_AMYOTROPHIC_LATERAL17 0.3021739 1 1 G57 HSA05214_GLIOMA 58 0.31301776 1 1 G58 OXIDATIVE_PHOSPHORYLATION 47 0.3220272 1 1 G59 HSA00410_BETA_ALANINE_METABO22 0.3370392 1 1 G60 PHENYLALANINE_METABOLISM 19 0.33817428 1 1 G61 BILE_ACID_BIOSYNTHESIS 24 0.34522623 1 1 G62 EGFPATHWAY 27 0.34864217 1 1 G63 GLYCEROLIPID_METABOLISM 37 0.35768887 1 1 G64 MTORPATHWAY 22 0.36680055 1 1 G65 NUCLEAR_RECEPTORS 37 0.36735904 1 1 G66 HSA00350_TYROSINE_METABOLISM40 0.36913556 1 1 G67 ALKPATHWAY 32 0.37270394 1 1 G68 HSA00561_GLYCEROLIPID_METABO 41 0.3845868 1 1 G69 HSA04662_B_CELL_RECEPTOR_SIGN57 0.38791186 1 1 G70 HSA00361_GAMMA_HEXACHLOROC17 0.39283141 1 1 G71 HSA00020_CITRATE_CYCLE 23 0.40391847 1 1 G72 GLUTATHIONE_METABOLISM 19 0.4129185 1 1 G73 KREBS_TCA_CYCLE 25 0.42316785 1 1 G74 GLYCEROPHOSPHOLIPID_METABOLI 40 0.42335045 1 1 G75 IL2PATHWAY 22 0.42562142 1 1 G76 HISTIDINE_METABOLISM 23 0.42697427 1 1 G77 HSA00640_PROPANOATE_METABOL26 0.43238962 1 1 G78 SIG_CHEMOTAXIS 40 0.44251284 1 1 G79 GLEEVECPATHWAY 22 0.4430708 1 1 G80 GLYCOLYSIS_AND_GLUCONEOGENE 37 0.45168468 1 1 G81 HSA00480_GLUTATHIONE_METABO 22 0.4627211 1 1 G82 LYSINE_DEGRADATION 26 0.46282783 1 1 G83 PORPHYRIN_AND_CHLOROPHYLL_M16 0.49036533 1 1 G84 SIG_PIP3_SIGNALING_IN_B_LYMPH 32 0.4950615 1 1 G85 BADPATHWAY 22 0.4986039 1 1 G86 GPCRDB_CLASS_B_SECRETIN_LIKE 20 0.5072234 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 2 of 4 Table.htm 2/24/11 1:12 PM
G87 GLUCONEOGENESIS 47 0.5104441 1 1 G88 GLYCOLYSIS 47 0.5104441 1 1 G89 HSA00340_HISTIDINE_METABOLISM27 0.5157876 1 1 G90 HSA00190_OXIDATIVE_PHOSPHORY 84 0.5371835 1 1 G91 HSA00150_ANDROGEN_AND_ESTRO30 0.5377873 1 1 G92 HSA02010_ABC_TRANSPORTERS_GE34 0.5439453 1 1 G93 CITRATE_CYCLE_TCA_CYCLE 18 0.54495376 1 1 G94 HSA04360_AXON_GUIDANCE 97 0.5492591 1 1 G95 HSA04730_LONG_TERM_DEPRESSIO66 0.5500296 1 1 G96 HSA05223_NON_SMALL_CELL_LUN 50 0.56373036 1 1 G97 ST_GAQ_PATHWAY 26 0.5679984 1 1 G98 UREA_CYCLE_AND_METABOLISM_O15 0.5878378 1 1 G99 HSA00591_LINOLEIC_ACID_METABO20 0.59092677 1 1 G100 HSA00860_PORPHYRIN_AND_CHLO 25 0.60117364 1 1 G101 OVARIAN_INFERTILITY_GENES 23 0.6075899 1 1 G102 HSA00010_GLYCOLYSIS_AND_GLUC 51 0.6103187 1 1 G103 PITX2PATHWAY 16 0.61235315 1 1 G104 PGC1APATHWAY 21 0.61577463 1 1 G105 MCALPAINPATHWAY 24 0.62054765 1 1 G106 RHOPATHWAY 29 0.6226415 1 1 G107 PAR1PATHWAY 19 0.62805235 1 1 G108 GLYCOSPHINGOLIPID_METABOLISM 20 0.63768417 1 1 G109 CHREBPPATHWAY 16 0.63795716 1 1 G110 GAMMA_HEXACHLOROCYCLOHEXA 23 0.6449454 1 1 G111 HSA00903_LIMONENE_AND_PINENE19 0.64788735 1 1 G112 ST_ADRENERGIC 34 0.6610236 1 1 G113 HSA04520_ADHERENS_JUNCTION 67 0.6620074 1 1 G114 SIG_CD40PATHWAYMAP 31 0.66494846 1 1 G115 CREBPATHWAY 26 0.6693612 1 1 G116 ECMPATHWAY 22 0.67427343 1 1 G117 HSA04070_PHOSPHATIDYLINOSITOL61 0.6748778 1 1 G118 GLUTAMATE_METABOLISM 19 0.6842767 1 1 G119 MEF2DPATHWAY 17 0.6849205 1 1 G120 HSA05210_COLORECTAL_CANCER 73 0.68915474 1 1 G121 RASPATHWAY 22 0.692607 1 1 G122 METPATHWAY 35 0.6958948 1 1 G123 NO1PATHWAY 25 0.6975284 1 1 G124 ALANINE_AND_ASPARTATE_METAB 17 0.7022045 1 1 G125 HCMVPATHWAY 15 0.71464896 1 1 G126 ST_MYOCYTE_AD_PATHWAY 24 0.72723675 1 1 G127 PTENPATHWAY 16 0.7310102 1 1 G128 TOB1PATHWAY 17 0.7311508 1 1 G129 STATIN_PATHWAY_PHARMGKB 15 0.7392734 1 1 G130 ST_JNK_MAPK_PATHWAY 38 0.7516953 1 1 G131 NKCELLSPATHWAY 18 0.767501 1 1 file:///Users/sayan/Desktop/Qing/Table.htm Page 3 of 4 Table.htm 2/24/11 1:12 PM
G132 STRIATED_MUSCLE_CONTRACTION 32 0.7687168 1 1 G133 HSA00980_METABOLISM_OF_XENO 40 0.7700956 1 1 G134 HDACPATHWAY 28 0.7715245 1 1 G135 HSA00251_GLUTAMATE_METABOLI 23 0.7743562 1 1 G136 ERK5PATHWAY 17 0.7773992 1 1 G137 RARRXRPATHWAY 15 0.78170115 1 1 G138 HSA04742_TASTE_TRANSDUCTION 22 0.78801936 1 1 G139 HSA05211_RENAL_CELL_CARCINOM61 0.78884465 1 1 G140 TCRPATHWAY 42 0.7993656 1 1 G141 HSA04350_TGF_BETA_SIGNALING_P78 0.8103205 1 1 G142 NGFPATHWAY 19 0.8139898 1 1 G143 STARCH_AND_SUCROSE_METABOLI 23 0.81628925 1 1 G144 SMALL_LIGAND_GPCRS 16 0.82680374 1 1 G145 HSA04720_LONG_TERM_POTENTIAT63 0.8346207 1 1 G146 NOS1PATHWAY 21 0.83827496 1 1 G147 HSA04540_GAP_JUNCTION 75 0.8431147 1 1 G148 PEPTIDE_GPCRS 59 0.84393066 1 1 G149 HSA00602_GLYCOSPHINGOLIPID_BI 18 0.846215 1 1 G150 SA_TRKA_RECEPTOR 16 0.85183805 1 1 G151 CARDIACEGFPATHWAY 16 0.87721777 1 1 G152 CALCINEURINPATHWAY 17 0.88851684 1 1 G153 NFATPATHWAY 46 0.9112729 1 1 G154 HSA04140_REGULATION_OF_AUTO 23 0.91395485 1 1 G155 ST_WNT_BETA_CATENIN_PATHWAY23 0.91791046 1 1 G156 SIG_INSULIN_RECEPTOR_PATHWAY 47 0.918064 1 1 G157 HSA00562_INOSITOL_PHOSPHATE_ 36 0.92054415 1 1 G158 HSA04012_ERBB_SIGNALING_PATH 78 0.92494136 1 1 G159 BCRPATHWAY 33 0.9293607 1 1 G160 HSA04530_TIGHT_JUNCTION 100 0.93740124 1 1 G161 HSA04912_GNRH_SIGNALING_PATH81 0.93878776 1 1 G162 AT1RPATHWAY 33 0.9481038 1 1 G163 GPCRPATHWAY 33 0.94877505 1 1 G164 HSA00500_STARCH_AND_SUCROSE 44 0.95963025 1 1 G165 SIG_PIP3_SIGNALING_IN_CARDIAC_ 62 0.9871668 1 1
file:///Users/sayan/Desktop/Qing/Table.htm Page 4 of 4 Supporting Information Click here to download Supporting Information: Sup.docx
Response to reviews Click here to download Other: Response_to_review.doc