Co-Expression Analysis of RNA-Sequence Data from Parkinson’S Disease Patients Akilina Wimalarasan
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Co-expression Analysis of RNA-sequence Data from Parkinson's Disease Patients Akilina Wimalarasan Department of Informatics-Bioinformatics University of Bergen Norway June 2020 1 2 Contents Abstract 5 Acknowledgments 5 1 Introduction 6 1.1 Parkinson's Disease . .6 1.1.1 Symptoms . .7 1.1.2 Genetics of Parkinson's Disease . .7 1.1.3 Transcriptomics in PD . .9 1.1.4 Molecular Factors of Parkinson's Disease . 10 1.2 Co-expression Analysis . 12 1.2.1 Co-expression Networks . 12 1.2.2 Input Data for Co-expression Networks . 14 1.2.3 Network Construction . 14 1.2.4 Identification of Modules by Clustering . 15 1.2.5 Block-wise Network Construction . 15 1.2.6 Gene Ontology . 16 1.2.7 Kyoto Encyclopedia for Genes and Genomes . 17 1.2.8 Module Evaluation and Analysis . 19 1.2.9 Differential Co-expression Analysis . 20 1.3 Personalized Medicine . 20 1.3.1 Personalized Medicine in Parkinson's Disease . 21 2 Aim of Study 22 3 Methods 23 3.1 Data . 23 3.1.1 Quality Controlling and Filtering . 23 3.1.2 Over-representation analysis of Gene Ontologies . 25 3.2 Network Construction and Module Detection . 26 3.2.1 Threshold . 26 3.2.2 Topological Overlap Matrix . 26 3.2.3 Modules . 27 3.3 Visualizing . 29 3.4 Evaluation . 30 3.4.1 Module Adjacency Heatmap . 30 3.4.2 Correspondence Matrix . 30 3.4.3 Module Preservation Statistics . 31 3.5 Analysis of Interesting Modules . 31 3.5.1 ConsensusPathDB . 32 3.5.2 ClueGO-Network of Pathways . 32 3.5.3 Module network visualization . 33 3 4 Results 37 4.1 Data . 37 4.2 Over-represented Gene Ontologies . 37 4.3 Constructing the Network . 38 4.4 Evaluating the Modules . 40 4.4.1 Module Eigengene Heatmap . 40 4.4.2 Module Correspondence Matrix . 43 4.4.3 Module Preservation . 44 4.4.4 Interesting Modules . 46 4.5 ConsensusPathDB . 46 4.5.1 The Pink Modules . 46 4.5.2 The Black Modules . 47 4.6 ClueGo . 47 4.6.1 Pink Modules . 49 4.6.2 Black Modules . 49 4.7 Module Network-Cytoscape . 52 4.7.1 Identifying Genes by Analyzing Betweenness Centrality Measures . 52 4.8 Interesting Genes . 54 4.8.1 Pink Module . 54 4.8.2 Black Module . 56 5 Discussion 57 5.1 Functions of Network Construction . 57 5.2 Evaluating the Modules . 58 5.3 Tools............................................. 58 5.3.1 ConsensusPathDB . 59 5.3.2 ClueGO . 59 5.3.3 Cytoscape . 60 5.4 Evaluating Results . 60 5.4.1 Modules . 60 5.4.2 ConsensusPathDB . 61 5.4.3 Module Network Analysis . 61 5.4.4 The Interesting Genes . 62 5.5 Personalized Medicine . 62 5.6 Further Study . 63 6 Conclusion 63 Glossary 66 References 71 A Appendix 72 A.1 ConsensusPathDB outputs . 72 A.2 Module networks-cytoscape . 89 A.3 R-files . 105 4 List of Figures 1 Neurodegeneration-illustration . .7 2 Molecular dysfunctions . 10 3 Three steps of co-expression network . 13 4 Hierarchical clustering . 16 5 Gene Ontology . 17 6 Kyoto Encyclopedia of Genes and Genomes . 18 7 P4 medicine . 21 8 Example of sample clustering . 24 9 Example of scale-free fit index plot . 27 10 Example of module eigengene tree . 28 11 Example of dendrogram . 28 12 Example of heatmap visualization . 29 13 Example of module eigengene adjacency heatmap . 31 14 ClueGO-Kappa score . 34 15 ClueGO Example . 35 16 Flow of study . 36 17 Over-represented gene ontology terms . 38 18 Results-Soft threshold . 39 19 Results-Module eigenegene trees . 40 20 Results-Dendrogram . 41 21 Results-Network heatmaps . 42 22 Results-Module eigengene heatmap . 43 23 Results-Correspondence matrix . 44 24 Results-Module preservation statistics . 45 25 Results-ClueGO . 48 26 Results-ClueGO-oxidative phosphorylation . 50 27 Results-Cytoscape network visualization . 53 List of Tables 1 Monogenic Parkinson genes . .8 2 Results-Parkinson's genes VS Alzheimers Genes . 51 3 Results-Identified genes in this study . 55 4 Functions of WGCNA . 57.