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