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Tmm: Analysis of Multiple Microarray Data Sets

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

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Tmm: Analysis of Multiple Microarray Data Sets

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

  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 KietHyun for curating all the biomarker data that was used for test queries.

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