Title | A variational Bayes discrete mixture test for rare variant association. |
Publication Type | Journal Article |
Year of Publication | 2014 |
Authors | Logsdon 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 Authors | Kooperberg C |
Corporate Authors | NHLBI GO Exome Sequencing Project |
Journal | Genet Epidemiol |
Volume | 38 |
Issue | 1 |
Pagination | 21-30 |
Date Published | 2014 Jan |
ISSN | 1098-2272 |
Keywords | African 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. |
DOI | 10.1002/gepi.21772 |
Alternate Journal | Genet Epidemiol |
PubMed ID | 24482836 |
PubMed Central ID | PMC4030763 |
Grant List | RC2 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 |