JSM Activity #373

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Activity ID:  373
Title
* ! Assessing Differential Gene Expression from Microarray Studies
Date / Time / Room Sponsor Type
08/15/2002
8:30 AM - 10:20 AM
Room: H-Beekman Parlor 		Biometrics Section*, Biopharmaceutical Section*, ENAR, Section on Statistical Computing* Topic Contributed
Organizer: Mark Segal, University of California, San Francisco
Chair: Mike West, Duke University
Discussant: 9:55 AM - Mark Segal, University of California, San Francisco    
Floor Discussion 10:15 AM
Description

A fundamental question in microarray gene expression studies is how to identify differentially expressed genes in the face of many sources of variation and simultaneous measurement of thousands of genes. The speakers propose empirical Bayes approaches and new formulations for evaluating false positive rates.
  300202  By:  Charles  Kooperberg 8:35 AM 08/15/2002
Identifying Possibly Positive Genes in Complex Microarray Studies

  300201  By:  John D. Storey 8:55 AM 08/15/2002
Using False Discovery Rates in DNA Microarrays

  300250  By:  Christina   Kendziorski 9:15 AM 08/15/2002
Experimental Design Issues Affecting the Assessment of Differential Expression

  300527  By:  Debashis  Ghosh 9:35 AM 08/15/2002
Meta-analysis of Microarray Data for Prostate Cancer Studies

JSM 2002

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Revised March 2002