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