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MetaCore data analysis suite and MetaCore data analysis suite and functional analysisfunctional analysis
Ying-Fan Chen, Ph. D.Ying-Fan Chen, Ph. D.
Feb. 5, 2010Feb. 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 TargetsCompound scoring
一般 Array Data 分析流程
Differentially expressed genes, proteins (normalization, QC)
Analysis:Networks, pathways,
Statistics on functional categories
Prioritized gene listsGenes 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
ResolutionExperiment 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
Agilent Affymetrix Proteomic SAGE
Concurrent visualization of different data types, experiments
OutlineIntroduction
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/
使用者電腦設定
OutlineIntroduction
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
http://training.genego.com/
http://training.genego.com/
1. 上傳檔案 藍色資料夾2. 下載 gene list
OutlineIntroduction
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?
往下拉!
12 genes
Analysis data
GeneGo Diseases (by Biomarkers)
Analysis data demo2
OutlineIntroduction
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
OutlineIntroduction
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…
OutlineIntroduction
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