Abstract #301599

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JSM 2002 Abstract #301599
Activity Number: 283
Type: Contributed
Date/Time: Wednesday, August 14, 2002 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Stat. Sciences*
Abstract - #301599
Title: Finding Significantly Differentially Expressed Genes
Author(s): Tanzy Love*+
Affiliation(s): Iowa State University
Address: 140 University Village Apt E, Ames, Iowa, 50010, USA
Keywords: Hierarchical Models ; Gene Expression ; E. coli
Abstract:

This paper examines part of the gene expression problem. Scientists are interested in how gene expression levels may vary under different treatments. They want to know which genes are expressed significantly differently under treatment conditions. The model used is the Bayesian hierarchical model proposed by Newton et al. in JCB 2001. This Gamma-Gamma-Bernoulli model leads to a criterion for classifying genes as significantly differentially expressed and an estimate of the proportion of genes that are differentially expressed. The variability of the classification as significantly differentially expressed is explored through simulation from the posterior predictive distribution of the model. Several data sets of open frames from E. coli bacteria are examined.

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