This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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132
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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ENAR
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Abstract - #307561 |
Title:
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A Multivariate Penalized Regression Method for eQTL Mapping
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Author(s):
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Ting-Huei Chen*+ and Wei Sun and Fred Wright
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Companies:
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The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill
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Address:
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, , 27599-7420,
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Keywords:
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Adaptive Lasso ;
Iterative Adaptive Lasso ;
multiple loci mapping ;
gene expression QTL (eQTL) ;
multivariate penalized regression
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Abstract:
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A main goal of expression quantitative trait locus (eQTL) studies is to dissect the genetic factors contributing to the variation of gene-expression. In most studies, tens of thousands of expression transcripts and genetic markers are measured. One common strategy is to analyze each transcript separately. However, it is well-known that several genes could be co-regulated and linked to some common eQTLs. The trait-by-trait mapping strategy fails to take into account the correlation between transcripts, which might lead to a loss of power. Here, we propose a multivariate penalized regression method for eQTL mapping that incorporates the correlation structure among transcripts and is applicable for the high dimension low sample size setting. Extensive simulations and real data studies show the superior performance of our method on the improvement in power and precision of eQTL mapping.
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