bioinformaticspipelinesforanalyzingisrcedatasetstoanswerkeysystemsbiologyquestions课件

Bioinformatics Pipelines for Analyzing ISRCE Datasets to Answer Key Systems Biology Questions,Yuriy Gusev Clinical Research Informatics Georgetown/Lombardi,Bioinformatics Analysis Pipeline,Raw Data Sets: public or local Gene Expression, DNA copy number, microRNA expression ,Data Proccessing: Uniform Signal Extraction, Normalization, Quality Control,Group Comparison Based on Clinical Attributes: Statistical Tests, Cluster Analysis, Principal Components Analysis, Classification (PUG-SVM),Advanced Analysis: Functional profiling; Pathway Analysis, Network Analysis, Machine Learning /Classification,Biological Interpretation,Experimental Or In Silico Validation,Novel Hypothesis,Study/Data Inventory,Breast Cancer Studies Total Cases: 1538+,Case Study: Loi et al.,Additional Studies: Assessment in Progress (Rebecca Riggins),Case Study (Loi et al.): Differential Gene Expression Clinical Outcome: five year DMFS,Data Analysis Details: Two options for processing: Original Affymetrix Probes Sets: Multiple Probe Sets per gene Custom Chip Definition Files (CDFs): Single Probe Set per gene (Bioconductor),Quality Control : Checking for outliers,Group Comparison: DMFS5years T-test with multiple testing correction: P0.05 controlling False Discovery Rate FDR5% Results: 252 differentially expressed genes (DEGs): 129Up; 123Down,Systems Biology Analysis: Functional profiling of DEGs - Gene Set Enrichment Analysis (GSEA algorithm MIT): 10 Pathways Rich collection of functionally related sets of genes (curated); Pathways from multiple open sources (KEGG, Biocarta, etc) - Gene Ontology Analysis (Pathway Studio): Top 20 Biological processes Pathway Enrichment Analysis Pathway Studio (4); Ingenuity (10) Regulatory Networks Enrichment: Transcription Factors, microRNA,Gene Set Enrichment Analysis (GSEA),Gene Set Enrichment Analysis (GSEA) Matrix View,Estrogen Signaling in Breast Cancer,In Progress,Tabular Format,Interactive Pathway,Pathway Analysis II : Pathway Studio (Ariadne),Significantly Enriched Pathways,Functional Profiling of Differentially Expressed Genes: Gene Ontology Enrichment Analysis,Top 3 Biological Processes,Gene Ontology Enrichment Analysis Next 10 categories: All related to Mechanisms of Mitosis,Mitosis Regulation Pathways: Mitotic Role of Polo-Like Kinase,STRING: Known Protein-Protein Interactions Network Based on 252 DEGs from Loi data analysis,Regulation of Mitosis,Regulatory Networks Enrichment Analysis I: Transcription Factors Expression Targets Enrichment with DEGs from Loi study (p0.05),Top 10 TFs,Regulatory Networks Enrichment Analysis II: microRNA known targets microRNA-regulated networks enriched with DEGs/Loi Study (p0.05),All enriched miRNA networks,Disease Ontology gene associations (DOLite),Summary,Bioinformatics Analysis Pipeline: uniform processing (R, Bioconductor) and analysis using caBIG tools and methods: Bioconductor, GSEA, Growing collection of uniformly processed public datasets Case Study: Loi et al, 5year DMFS - Identified 252 differentially expressed genes Gene Set and Pathway Analysis identified small subset of specific pathways related to cell cycle and mitosis regulation, Estrogen Receptor signaling and several others Functional Profiling using Gene Ontology Enrichment and Regulatory Sub-networks Enrichment analysis allows to narrow down specific biological processes and molecular regulators (Transcription Factors and microRNAs) that are most likely factors affecting expression of identified DEGs and could be candidates for follow-up experiments In Progress : classification algorithm (PUG-SVM) and advanced network ana