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Plos Computational Biology : Leveraging Prior Information to Detect Causal Variants Via Multi-variant Regression, Volume 9

By Long, Nanye

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Book Id: WPLBN0003952567
Format Type: PDF eBook :
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Reproduction Date: 2015

Title: Plos Computational Biology : Leveraging Prior Information to Detect Causal Variants Via Multi-variant Regression, Volume 9  
Author: Long, Nanye
Volume: Volume 9
Language: English
Subject: Journals, Science, Computational Biology
Collections: Periodicals: Journal and Magazine Collection (Contemporary), PLoS Computational Biology
Historic
Publication Date:
Publisher: Plos

Description
Description : Although many methods are available to test sequence variants for association with complex diseases and traits, methods that specifically seek to identify causal variants are less developed. Here we develop and evaluate a Bayesian hierarchical regression method that incorporates prior information on the likelihood of variant causality through weighting of variant effects. By simulation studies using both simulated and real sequence variants, we compared a standard single variant test for analyzing variant-disease association with the proposed method using different weighting schemes. We found that by leveraging linkage disequilibrium of variants with known GWAS signals and sequence conservation (phastCons), the proposed method provides a powerful approach for detecting causal variants while controlling false positives.

 

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