1. Tmm: Analysis of Multiple Microarray Data Sets Richard Moffitt Georgia Institute of Technology 29 June, 2006

2. Goal Use 60 large human microarray datasets. (3924 arrays) Find reliably coexpressed genes. http://benzer.ubic.ca/cgi-bin/find-links.cgi –(just google ‘tmm microarray’)

3. Usage Case Query by gene or probe ID. Set stringency level.

4. How it Works Looks for genes that coexpress with the queried-for gene. –correlates gene expression profiles Stringency requirement eliminates weak links.

5. Our Query RAP1GSD1, a biomarker form Chang et al

6. 2 minutes later…

7. Our Results List of linked genes and some statistics.

8. Visualization Visualizations of coexpresed gene profiles for each dataset used.

9. Query #2 LETMD1, a biomarker from Citation Spira A, Am J Respir Cell Mol Biol. 2004 Phenotypes_Being_Studied No or mild emphysema, severe emphysema Chip_Platform GPL96: Affymetrix GeneChip Human Genome U133 Array Set HG-U133A for 712X712

10. Results #2 :

11. Why? Our first query was from one of the datasets used by Tmm.

12. Synonym Search

13. Conclusion Useful to make a small list of probable targets. Useful for some validation? –Similar to GOMiner validation. –Speed will inhibit this. Semantics is a barrier to usefulness.

14. Acknowledgements Thanks to: Deepak Sambhara JT Torrance Lauren Smalls-Mantey Malcolm Thomas Randy Han and Kiet Hyun for curating all the biomarker data that was used for test queries.