This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 157
Type: Topic Contributed
Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #307958
Title: Bias Correction and Bayesian Analysis of Digital Gene Expression Libraries
Author(s): Russell L. Zaretzki*+ and Michael A. Gilchrest
Companies: University of Tennessee and University of Tennessee
Address: 328 SMC, Knoxville , TN, 37996-0532, USA
Keywords: Digital Gene Expression ; Gibbs Sampling ; Differential Expression ; MCMC ; Microarray
Abstract:

Tag-based techniques such as Digital Gene Expression(DGE) are commonly used to sample the mRNA pool of an organism's transcriptome. Incomplete digestion during the tag formation process may allow for multiple tags to be generated from a given mRNA transcript. The probability of forming a tag varies with its relative location. As a result, the observed tag counts represent a biased sample of the actual transcript pool. Several Bayesian inference algorithms that account for tag formation effects are compared. The accuracy of inferences when using a particular non-informative prior is found to depend on the expression level of a given gene. Calculations demonstrate the potential for false positive and negative findings due to variation in tag formation probabilities across samples when testing for differential expression.


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