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

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Presentation on theme: "MetaCore data analysis suite and functional analysis Ying-Fan Chen, Ph. D. Feb. 5, 2010."— Presentation transcript:

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

2 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

3 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

4 “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

5 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

6 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

7 AgilentAffymetrixProteomicSAGE Concurrent visualization of different data types, experiments

8 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 http://www.binfo.ncku.edu.tw/2010_genomics/

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10 使用者電腦設定

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12 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

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19 上傳成功!

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21 early s phase list

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32 http://training.genego.com/

33 1. 上傳檔案  藍色資料夾 2. 下載 gene list

34 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

35 Analysis data 分析前注意事項

36 Remove data from Exp. File to yourself file

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39 GS875 Active Data

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41 Analysis data GeneGo Pathway Maps

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44 如何找出這些 genes list?

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46 12 genes

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48 Analysis data GeneGo Diseases (by Biomarkers)

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52 Analysis data  demo2

53 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

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59 請一直按著 Ctrll 鍵

60 workflow

61 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

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69 Save Publish Map…

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71 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

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