1 / 14

Analysis of Multiple Microarray Data Sets Using TMM: Coexpressed Gene Identification

Explore 60 large human microarray datasets to find reliably coexpressed genes. Access query results and visualize coexpressed gene profiles efficiently. Utilize TMM for robust analysis.

emoreno
Télécharger la présentation

Analysis of Multiple Microarray Data Sets Using TMM: Coexpressed Gene Identification

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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.

More Related