1. Improving gene expression similarity measurement using pathway-based analytic dimension Changwon Keum BMDRC

2. Accumulated gene expression data in public repository GEO, NCBI

3. Search the database * Search by annotation * Search by contents

4. Dataset vs. individual sample( profile) Case Control Microarray database search Data set Individual profiles Data set level Similarity measure Profile level Similarity measure search

5. Raw gene expression profile based similarity search Used by Cellmontage –Spearman correlation coefficient Limitation –Cross-platform comparison –Cross-experiment comparison S1S2d G1514 G2321 G3132 G4242 G5451 S1S2 G1630 G21625 G32215 G42010 G5105

6. Pathway expression profile based similarity measure G1G2G3. Pathway1Pathway2Pathway3 Pathway1Pathway2Pathway3 Pathway1Pathway2Pathway3 Step1. Converting to pathway Expression profile Step2. Spearman Correlation Test

7. Cell type classification SampleExperim ent PlatformCell type Sam1Exp1Plat1Breast Sam2Exp1Plat1Breast Sam3Exp1Plat2Breast Sam4Exp2Plat3Breast Sam5Exp2Plat3Breast Samples with cell type –Annotated by Cellmontage group –For 42 cell type with multiple samples Query Cross-platform Cross-experiment

8. Classification accuracy

9. CGSEP vs. PEPC Thalamus (all) Liver(Cross-platform)

10. Similarity score for TP?

11. Details of cross-experiment classification

12. GEFERENCE Reference database of gene expression –Search similar gene expression profile –Meta analysis

13. Marker Validation Extract sample Patient GEFERENCE Gene expression profiling Search Matched reference individual with Clinical information

14. Acknowledgement Jung Hoon Woo Members at BMDRC KFDA for funding Thanks for your attention!!