JSM Activity #93

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Activity ID:  93
Title
* ! Determining the Statistical Significance of Observed Changes in Gene Expression Data
Date / Time / Room Sponsor Type
08/12/2002
10:30 AM - 12:20 PM
Room: S-New York Ballroom B 		Biometrics Section*, Biopharmaceutical Section*, ENAR, Section on Statistical Computing* Topic Contributed
Organizer: Dan Nettleton, Iowa State University
Chair: Guosheng Yin, University of North Carolina
Discussant:  
Floor Discussion 12:15 PM
Description

Talks in this session address the design and analysis of experiments aimed at uncovering information about gene function through the use of microarray technology. The speakers in this session will discuss many important statistical issues including the efficient design of these expensive experiments, adjustments for multiple testing, proper accounting for random effects, and methods for gaining additional information by combining gene expression data with molecular marker data.
  301828  By:  Michael  Newton 10:35 AM 08/12/2002
Detecting Differential Expression with Semiparametric MixtureModels

  300252  By:  Russ  Wolfinger 10:55 AM 08/12/2002
Mixed Models for Microarrays

  300197  By:  Gary  Churchill 11:15 AM 08/12/2002
Statistical Design and Analysis for Gene Expression Microarrays

  301255  By:  Dan  Nettleton 11:35 AM 08/12/2002
A Comparison of Methods for Managing Type I Errors when Testing for Gene Expression Changes

  300198  By:  Rebecca W. Doerge 11:55 AM 08/12/2002
Microarray Analysis Meets Quantitative Trait Locus (QTL) Analysis

JSM 2002

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Revised March 2002