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Activity Number: 664
Type: Invited
Date/Time: Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
Sponsor: WNAR
Abstract - #307459
Title: Strategies for Detecting Allele-Specific Imbalance by Modifying Rare Variant Association Methods
Author(s): Sharon Lutz*+ and Tasha E. Fingerlin
Companies: Univ. of Colorado and University of Colorado Anschutz Medical Campus
Keywords: allele specific expression ; rare variants ; collapsing methods ; allele specific imbalance ; window-based approach ; Hidden Markov Models
Abstract:

In order to detect allele specific imbalance, one interesting approach proposed by Wagner et al collapses information across a window in order to increase power. Wagner et al used both z-score approaches and Hidden Markov Models. This raises the question: how would some of the standard collapsing methods used in the detection of rare variants compare to this method for detecting allele specific imbalance? To answer this question, we modified several standard collapsing methods for detecting rare variants to be applicable for the detection of allele specific imbalance, such as the Cohort Allelic Sum Test (CAST), the Combined Multivariate and Collapsing Method (CMC), the Weighted Sum Test (WST). We then conducted simulations studies of these modified methods for detecting rare variants against Wagner et al's approach to see which method has the most power to detect allele specific imbalance across a pre-specified window.

Reference: Wagner JR, Ge B, Pokholok D, Gunderson KL, Pastinen T, et al. (2010) Computational Analysis of Whole-Genome Differential Allelic Expression Data in Human. PLoS Comput Biol 6(7): e1000849


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