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A variational Bayes discrete mixture test for rare variant association.

TitleA variational Bayes discrete mixture test for rare variant association.
Publication TypeJournal Article
Year of Publication2014
AuthorsLogsdon BA, Dai JY, Auer PL, Johnsen JM, Ganesh SK, Smith NL, Wilson JG, Tracy RP, Lange LA, Jiao S, Rich SS, Lettre G, Carlson CS, Jackson RD, O'Donnell CJ, Wurfel MM, Nickerson DA, Tang H, Reiner AP
Secondary AuthorsKooperberg C
Corporate AuthorsNHLBI GO Exome Sequencing Project
JournalGenet Epidemiol
Volume38
Issue1
Pagination21-30
Date Published2014 Jan
ISSN1098-2272
KeywordsAfrican Americans, Algorithms, Bayes Theorem, Exome, Female, Genetic Association Studies, Genetic Variation, Humans, Male, Models, Genetic, Mutation, Missense, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Research Design, Sequence Analysis, DNA, Software, United States, von Willebrand Factor
Abstract

Recently, many statistical methods have been proposed to test for associations between rare genetic variants and complex traits. Most of these methods test for association by aggregating genetic variations within a predefined region, such as a gene. Although there is evidence that "aggregate" tests are more powerful than the single marker test, these tests generally ignore neutral variants and therefore are unable to identify specific variants driving the association with phenotype. We propose a novel aggregate rare-variant test that explicitly models a fraction of variants as neutral, tests associations at the gene-level, and infers the rare-variants driving the association. Simulations show that in the practical scenario where there are many variants within a given region of the genome with only a fraction causal our approach has greater power compared to other popular tests such as the Sequence Kernel Association Test (SKAT), the Weighted Sum Statistic (WSS), and the collapsing method of Morris and Zeggini (MZ). Our algorithm leverages a fast variational Bayes approximate inference methodology to scale to exome-wide analyses, a significant computational advantage over exact inference model selection methodologies. To demonstrate the efficacy of our methodology we test for associations between von Willebrand Factor (VWF) levels and VWF missense rare-variants imputed from the National Heart, Lung, and Blood Institute's Exome Sequencing project into 2,487 African Americans within the VWF gene. Our method suggests that a relatively small fraction (~10%) of the imputed rare missense variants within VWF are strongly associated with lower VWF levels in African Americans.

DOI10.1002/gepi.21772
Alternate JournalGenet Epidemiol
PubMed ID24482836
PubMed Central IDPMC4030763
Grant ListRC2 HL102923 / HL / NHLBI NIH HHS / United States
RC2 HL-102924 / HL / NHLBI NIH HHS / United States
RC2 HL102926 / HL / NHLBI NIH HHS / United States
P01 CA053996 / CA / NCI NIH HHS / United States
P01 CA-53996 / CA / NCI NIH HHS / United States
RC2 HL-102926 / HL / NHLBI NIH HHS / United States
RC2 HL-102923 / HL / NHLBI NIH HHS / United States
RC2 HL102924 / HL / NHLBI NIH HHS / United States
R01 HL114901 / HL / NHLBI NIH HHS / United States
R01 HG-006124 / HG / NHGRI NIH HHS / United States
R01 HG006124 / HG / NHGRI NIH HHS / United States
RC2 HL103010 / HL / NHLBI NIH HHS / United States
R01 HL-114901 / HL / NHLBI NIH HHS / United States
RC2 HL-102925 / HL / NHLBI NIH HHS / United States
RC2 HL102925 / HL / NHLBI NIH HHS / United States
RC2 HL-103010 / HL / NHLBI NIH HHS / United States