[Colloquium] Sayan Mukherjee's talk on February 18, 2004

[Margery Ishmael]

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DEPARTMENTS OF COMPUTER SCIENCE
& STATISTICS - TALK

Date: Wednesday, February 18, 2004
Time: 2:30 p.m.
Place: Ryerson 251
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Speaker:  SAYAN MUKHERJEE, MIT Cancer Genomics Group

Url:  http://www.ai.mit.edu/people/sayan/sayan.html

Title:   Gene Set Enrichment Analysis

Abstract:

The selection and analysis of differentially expressed gene profiles 
(markers) helps associate a biological phenotype with its underlying 
molecular mechanisms and provides valuable insights into the structure 
of pathways and cellular regulation. However, analyzing and 
interpreting a given list of gene markers to glean useful biological 
insights can be extremely challenging. This is in part due to the 
difficulty of objectively evaluating how well members of a given 
pathway or functional class of interest (Gene Set) are respresented in 
the markers list. To address this problem we introduce a statistical 
methodology called Gene Set Enrichment Analysis (GSEA) for determing 
whether a given Gene Set is over-represented or enriched in a Gene List 
of markers ordered by their correlation with a phenotype or class 
distinction of interest. The method is based upon a score computed as 
the maximum deviation of a non i.i.d. Brownian Bridge (in the same 
spirit as the Kolmogorov-Smirnov statistic) and uses permutation 
testing to assess significance. When multiple Gene Sets are tested 
simultaneously we propose two approaches to address the multiplicity: 
Validation GSEA which controls the Familywise error rate (FWER) and 
Discovery GSEA which controls the False Discovery rate (FDR). The 
utility of this procedure will be illustrated on a variety of 
biological examples

Host: The Department of Statistics

*Refreshments will follow the talk in Ryerson 255*