MetaCore data analysis suite and functional analysis Ying-Fan Chen, Ph. D. Feb. 5, 2010

Outline Introduction 由成大生資中心進入：使用前設定以及注意事項 簡介使用方法  試用帳號  實際操作 Upload Data  Analyze Data  快速 workflow  MapEditor

Outline Introduction 由成大生資中心進入：使用前設定以及注意事項 簡介使用方法  試用帳號  實際操作 Upload Data  Analyze Data  快速 workflow  MapEditor

“Knowledge-based” functional data analysis HTS, HCS Cancer relevant annotations, datatabases, Active cpds analysis screening Knowledge Base: - protein interactions - causative associations (gene-disease, cpd-disease) - pathways, protein complexes - ontologies Experimental data depository Data parsing, normalization Data analysis tools: EA, networks, interactome Biomarkers Targets Compound scoring

一般 Array Data 分析流程 Differentially expressed genes, proteins (normalization, QC) Analysis: Networks, pathways, Statistics on functional categories Prioritized gene lists Genes are functionally connected “Cut off” setting ( eg, log ratio; fold change)  eg, GeneSpring GX  eg, MetaCore

Functional analysis tools Enrichment analysis for gene, protein, compound sets –Hyper G, GSEA, GSA etc. –Multidimensional analysis: multiple ontologies GO processes GG processes Canonical pathways Diseases –Export of sub-sets for network analysis –Low resolution 1000 genes; Multiple sets Network analysis – Multiple pre-filters (species, interactions mechanisms, organelles etc.) – Parameters: enrichment with genes from set, canonical pathways, specific protein classes – Algorithms: SP, DI, AN, TFs, Receptors etc. – Statistics: hubs, preferred pathways etc. – Highest resolution: individual proteins or isoforms Interactome analysis – Whole-set analysis – Over- and underconnected nodes in the dataset Interactions neighborhood TFs, kinases, receptors, etc. – Scoring for interactions within set: FDR Resolution Experiment filters – Species, orthologs, localizations, tissues etc. – Custom list of targets, IDs “Most important” genes - Highly connected TFs, receptors, etc. -Hubs from important networks -Highest expressed/mutated genes

AgilentAffymetrixProteomicSAGE Concurrent visualization of different data types, experiments

Outline Introduction 由成大生資中心進入：使用前設定以及注意事項 簡介使用方法  試用帳號  實際操作 Upload Data  Analyze Data  快速 workflow  MapEditor

使用者電腦設定

Outline Introduction 由成大生資中心進入：使用前設定以及注意事項 簡介使用方法  試用帳號  實際操作 Upload Data  Analyze Data  快速 workflow  MapEditor

上傳成功！

early s phase list

1. 上傳檔案  藍色資料夾 2. 下載 gene list

Outline Introduction 由成大生資中心進入：使用前設定以及注意事項 簡介使用方法  試用帳號  實際操作 Upload Data  Analyze Data  快速 workflow  MapEditor

Analysis data 分析前注意事項

Remove data from Exp. File to yourself file

GS875 Active Data

Analysis data GeneGo Pathway Maps

如何找出這些 genes list?

12 genes

Analysis data GeneGo Diseases (by Biomarkers)

Analysis data  demo2

Outline Introduction 由成大生資中心進入：使用前設定以及注意事項 簡介使用方法  試用帳號  實際操作 Upload Data  Analyze Data  快速 workflow  MapEditor

請一直按著 Ctrll 鍵

workflow

Outline Introduction 由成大生資中心進入：使用前設定以及注意事項 簡介使用方法  試用帳號  實際操作 Upload Data  Analyze Data  快速 workflow  MapEditor

Save Publish Map…

Outline Introduction 由成大生資中心進入：使用前設定以及注意事項 簡介使用方法  試用帳號  實際操作 Upload Data  Analyze Data  快速 workflow  MapEditor