PDF Output of CLIC (clustering by inferred co-expression) Dataset: Num of genes in input gene set: 13 Total number of genes: 16493 CLIC PDF output has three sections: 1) Overview of Co-Expression Modules (CEMs) Heatmap shows pairwise correlations between all genes in the input query gene set. Red lines shows the partition of input genes into CEMs, ordered by CEM strength. Each row shows one gene, and the brightness of squares indicates its correlations with other genes. Gene symbols are shown at left side and on the top of the heatmap. 2) Details of each CEM and its expansion CEM+ Top panel shows the posterior selection probability (dataset weights) for top GEO series datasets. Bottom panel shows the CEM genes (blue rows) as well as expanded CEM+ genes (green rows). Each column is one GEO series dataset, sorted by their posterior probability of being selected. The brightness of squares indicates the gene's correlations with CEM genes in the corresponding dataset. CEM+ includes genes that co-express with CEM genes in high-weight datasets, measured by LLR score. 3) Details of each GEO series dataset and its expression profile: Top panel shows the detailed information (e.g. title, summary) for the GEO series dataset. Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Overview of Co-Expression Modules (CEMs) with Dataset Weighting Scale of average Pearson correlations Num of Genes in Query Geneset: 13. Num of CEMs: 1. 0.0 0.2 0.4 0.6 0.8 1.0 Rps29 Rps28 Fau Rps6 Mrps2 Rps18 Mrps6 Rps25 Gnb2l1 Mrps12 Dap3 Rps24 Rps16 Rps29 Rps28 CEM 1 (813 datasets) Fau Rps6 Mrps2 Rps18 Mrps6 Rps25 Singletons Gnb2l1 Mrps12 Dap3 Rps24 Rps16 Symbol Num ofCEMGenes:3.Predicted33.SelectedDatasets:813.Strength:4.4 CEM 1,Geneset"[G]smallribosomalsubunit",Page1 Tmsb4x Cox6a1 Rps3a1 Atp5g3 Cox4i1 Eef1b2 Rpl10a Rpl13a Rpl37a Rpl18a Rps19 Rps11 Rps4x Uba52 Rps28 Rps29 Actg1 Rplp0 Rplp2 Nme2 Rpl27 Rpl7a Rpl26 Rpl38 Rps2 Rps7 Rps5 Naca Eif3f Rpl7 Rpl8 Rpl6 Rpl4 Eif3i Eef2 Fau 0.0 1.0 GSE46871 [6] GSE15610 [12] GSE7219 [12] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE32615 [10] GSE6785 [9] GSE4749 [6] GSE33471 [12] GSE22903 [24] GSE36530 [6] GSE14308 [12] GSE20727 [15] GSE23833 [12] GSE21944 [6] GSE2019 [12] GSE19286 [6] GSE39621 [51] GSE39897 [36] GSE2527 [6] GSE4288 [36] GSE47065 [8] GSE21143 [6] GSE24465 [6] GSE35844 [9] GSE10071 [10] GSE39592 [8] GSE6676 [8] GSE5497 [6] GSE8555 [8] GSE15458 [8] GSE36384 [12] GSE26745 [24] GSE13874 [14] GSE39082 [6] GSE5921 [6] GSE36618 [6] GSE32529 [224] GSE54581 [21] GSE41942 [6] GSE42061 [12] GSE16364 [6] GSE49346 [6] GSE14478 [7] GSE10552 [6] GSE33121 [10] GSE43620 [8] GSE58262 [18] GSE8503 [6] GSE10871 [32] GSE19687 [9] GSE34761 [8] GSE35825 [9] GSE17728 [12] GSE23178 [6] GSE35734 [6] GSE18010 [29] GSE3861 [6] GSE53299 [6] GSE19181 [6] GSE35318 [12] GSE42008 [6] GSE24726 [8] GSE13547 [12] GSE24437 [6] GSE6030 [6] GSE11358 [8] GSE12467 [6] GSE6084 [12] GSE38304 [8] GSE9978 [8] GSE58484 [15] GSE24695 [9] GSE31776 [10] GSE11149 [8] GSE6134 [7] GSE52474 [154] GSE58296 [9] GSE28093 [6] GSE42135 [42] GSE21900 [12] GSE11420 [15] GSE11044 [6] GSE11148 [6] GSE34206 [8] GSE6674 [15] GSE18115 [8] GSE34618 [7] GSE27717 [11] GSE2161 [8] GSE31086 [6] GSE19793 [32] GSE47421 [24] GSE18281 [33] GSE24789 [9] GSE19076 [12] GSE32903 [12] GSE37029 [15] GSE56755 [13] GSE10210 [16] GSE13805 [7] GSE11628 [12] GSE16210 [14] GSE51365 [28] GSE14672 [12] GSE32199 [6] GSE17097 [20] GSE36569 [6] GSE11766 [48] GSE27302 [16] GSE48811 [20] GSE7781 [12] GSE24873 [48] GSE7705 [10] GSE36414 [8] GSE6675 [8] GSE7605 [18] GSE12430 [21] GSE10216 [6] GSE31359 [8] GSE46094 [10] GSE8683 [11] GSE14698 [12] GSE23398 [7] GSE46242 [12] GSE30767 [8] GSE7810 [9] GSE11120 [10] GSE39375 [10] GSE6998 [32] GSE27378 [8] GSE38283 [7] GSE7111 [6] GSE47798 [30] GSE1999 [15] GSE21841 [18] GSE31598 [12] GSE11918 [9] GSE32102 [49] GSE13963 [15] GSE6259 [21] GSE14929 [38] GSE13690 [38] GSE20726 [9] GSE34423 [40] GSE43242 [10] GSE27675 [14] GSE6065 [100] GSE7683 [12] GSE49351 [6] GSE25140 [16] GSE26695 [20] GSE50439 [15] GSE48935 [12] GSE7657 [12] GSE40296 [6] CEM+ CEM GSE4656 [7] GSE9760 [12] GSE56492 [12] GSE12993 [6] GSE8836 [56] GSE21606 [6] 0.0 GSE15794 [6] GSE10954 [8] GSE54656 [27] Scale ofaveragePearsoncorrelations GSE42688 [8] GSE4043 [6] GSE18460 [16] GSE40412 [14] GSE34324 [12] GSE19272 [30] 0.2 GSE5035 [12] GSE26076 [12] GSE8682 [8] GSE51686 [9] GSE46185 [6] GSE56482 [8] GSE6591 [15] GSE35106 [9] GSE3822 [16] 0.4 GSE18587 [9] GSE6526 [16] GSE7487 [24] GSE35077 [26] GSE21033 [12] GSE13799 [18] GSE17553 [16] GSE10556 [6] GSE31646 [11] 0.6 GSE13259 [10] GSE9316 [12] GSE17102 [9] GSE11496 [16] GSE25828 [8] GSE6482 [9] GSE59319 [6] GSE35998 [20] GSE21711 [6] 0.8 GSE41895 [12] GSE26025 [12] GSE21272 [44] GSE4734 [61] Score 5.39 13.81 15.97 18.66 22.80 44.13 47.84 97.20 167.17 212.21 245.03 327.57 389.57 414.31 439.83 457.74 472.00 497.93 506.94 512.94 551.86 605.21 619.89 624.52 627.69 655.55 692.60 694.20 716.72 763.57 784.08 802.10 943.77 1.0 Notes GEO Series "GSE46871" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE46871 Status: Public on May 14 2013 Title: Hippocampal gene expression profiling of a model of Alzheimer`s Disease upon treatment with the ACE inhibitor captopril Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23959119 Summary & Design: Summary: Extracellular senile plaques of amyloid beta (Abeta) are a pathological hallmark in brain of patients with Alzheimer`s Disease (AD). Abeta is generated by the amyloidogenic processing of the amyloid precursor protein (APP). Concomitant to Abeta load, AD brain is characterized by an increase in protein level and activity of the angiotensin-converting enzyme (ACE). ACE inhibitors are a widely used class of drugs with established benefits for patients with cardiovascular disease. However, the role of ACE and ACE inhibition in the development of Abeta plaques and the process of AD-related neurodegeneration is not clear since ACE was reported to degrade Abeta. To investigate the effect of ACE inhibition on AD-related pathomechanisms, we used Tg2576 mice with neuron-specific expression of APPSwe as AD model. From 12 months of age, substantial Abeta plaque load accumulates in the hippocampus of Tg2576 mice as a brain region, which is highly vulnerable to AD-related neurodegeneration. The effect of central ACE inhibition was studied by treatment of 12 month-old Tg2576 mice for six months with the brain penetrating ACE inhibitor captopril. At an age of 18 months, hippocampal gene expression profiling was performed of captopril-treated Tg2576 mice relative to untreated 18 month-old Tg2576 controls with high Abeta plaque load. As an additional control, we used 12 month-old Tg2576 mice with low Abeta plaque load. Whole genome microarray gene expression profiling revealed gene expression changes induced by the brain-penetrating ACE inhibitor captopril, which could reflect the neuro-regenerative potential of central ACE inhibition. Overall design: Microarray gene expression profiling was performed of hippocampi isolated from aged, 18 month-old Tg2576 (APPSwe-transgenic) AD mice with high Abeta plaque load relative to age-matched Tg2576 mice, which were treated for 6 months with the centrally active ACE inhibitor captopril. Another study group consisted of 12 month-old Tg2576 mice with low Abeta plaque load. In total, three study groups were analyzed, i.e. (i) 18 month-old untreated Tg2576 mice with high Abeta plaque load, (ii) age-matched Tg2576 mice treated for 6 months with the brain-penetrating ACE inhibitor captopril (20 mg/kg body weight/day in drinking water), and (iii) untreated 12 month-old Tg2576 mice with low Abeta plaque load reflecting the time point when captopril treatment was initiated. Two biological replicates were made of each group, and total hippocampal RNA of four mice was pooled for one gene chip. Background corr dist: KL-Divergence = 0.0289, L1-Distance = 0.0256, L2-Distance = 0.0007, Normal std = 0.6941 0.592 Kernel fit Pairwise Correlations Normal fit Density 0.296 0.000 CEM 1 Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00 Pre-normalization Quantiles Hippocampus,Hippocampus, Hippocampus,Tg2576-APPSwe Hippocampus,Tg2576-APPSwe Hippocampus,Tg2576-APPSwe mice, Hippocampus,Tg2576-APPSwe 18 mice, month-old, Tg2576-APPSwe 18 mice, month-old, Tg2576-APPSwe with18 mice, month-old, high with18 mice,Abeta month-old, high [ ACE12 plaque mice,Abetamin month-old, inhibitor-treated-rep1 ACE12 load-rep1plaque month-old,] inhibitor-treated-rep2 with load-rep2 (0.113485) low with Abeta[ (0.195533) (0.0875443)lowmedium plaque Abeta (0.134632) load-rep1plaque load-rep2] (0.218563) (0.250242)[ max ] CEM 1 Rps29 12375.2 14976.7 24076.8 P ( S | Z, I ) = 1.00 Rps28 14336.5 16979.3 26885.3 Mean Corr = 0.99357 Fau 8290.9 9621.0 14102.9 Rpl38 15675.6 19214.5 28807.4 Rpl26 15073.9 17873.6 27509.8 Rpl18a 8685.9 10628.9 16424.2 Rpl37a 9947.9 11659.9 19225.9 Rps5 7671.9 9027.7 12613.7 CEM 1 + Rplp2 12205.7 15310.3 21225.1 Top 10 Genes Uba52 10119.0 11828.0 19404.2 Rpl7a 10525.7 13079.1 17966.5 Rps4x 10410.2 12306.3 18641.7 Rps7 11194.3 12860.6 18807.4 Null module Rps6 Mrps2 Rps18 Mrps6 Rps25 Gnb2l1 Mrps12 Dap3 Rps24 Rps16 GEO Series "GSE15610" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15610 Status: Public on Dec 22 2009 Title: Knockout of the selenocysteine tRNA (Trsp) gene in mouse macrophage Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19863805 Summary & Design: Summary: Comparative analysis of gene expression in bone marrow-derived macrophages (BMDM) from trsp knockout mice (Trspfl/fl-LysM-Cre+/-) and Control (Trspfl/fl-LysM-Cre-/-) mice.