Improving gene expression similarity measurement using

pathway-based analytic dimension

Changwon Keum

BMDRC

Accumulated gene expression data in public repository

• GEO, NCBI

# of Experiments sumitted to GEO database

14 113

665972

1489

2318

29262621

0

500

1000

1500

2000

2500

3000

3500

2001 2002 2003 2004 2005 2006 2007 2008

Years

Co

un

ts

Search the database

* Search by annotation

* Search by contents

Dataset vs. individual sample( profile)

Case Control

Microarraydatabase

search

Data set

Individual profiles

Data set level

Similarity measure

Profile level

Similarity measuresearch

Raw gene expression profile based similarity search

• Used by Cellmontage– Spearman correlation coefficient

• Limitation– Cross-platform comparison– Cross-experiment comparison

S1 S2 d

G1 5 1 4

G2 3 2 1

G3 1 3 2

G4 2 4 2

G5 4 5 1

S1 S2

G1 6 30

G2 16 25

G3 22 15

G4 20 10

G5 10 5

Pathway expression profile based similarity measure

G1 G2 G3 .

Pathway1 Pathway2 Pathway3

Pathway1 Pathway2 Pathway3

Pathway1 Pathway2 Pathway3

Step1.Convertingto pathwayExpressionprofile

Step2.SpearmanCorrelationTest

Cell type classification

Sample

Experiment

Platform

Cell type

Sam1 Exp1 Plat1 Breast

Sam2 Exp1 Plat1 Breast

Sam3 Exp1 Plat2 Breast

Sam4 Exp2 Plat3 Breast

Sam5 Exp2 Plat3 Breast

• Samples with cell type – Annotated by Cellmontage group– For 42 cell type with multiple samples

Query

Cross-platform

Cross-experiment

Classification accuracy

CGSEP vs. PEPC

Thalamus (all) Liver(Cross-platform)

Similarity score for TP?

Details of cross-experiment classification

GEFERENCE

• Reference database of gene expression– Search similar gene expression profile– Meta analysis

Marker Validation

Extract samplePatient

GEFERENCE

Gene expression profiling

Search

Matched reference individualwith Clinical information

Acknowledgement

• Jung Hoon Woo• Members at BMDRC• KFDA for funding

Thanks for your attention!!