Dataset Information

Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies.

ABSTRACT: We propose in this paper a unified approach for testing the association between rare variants and phenotypes in sequencing association studies. This approach maximizes power by adaptively using the data to optimally combine the burden test and the nonburden sequence kernel association test (SKAT). Burden tests are more powerful when most variants in a region are causal and the effects are in the same direction, whereas SKAT is more powerful when a large fraction of the variants in a region are noncausal or the effects of causal variants are in different directions. The proposed unified test maintains the power in both scenarios. We show that the unified test corresponds to the optimal test in an extended family of SKAT tests, which we refer to as SKAT-O. The second goal of this paper is to develop a small-sample adjustment procedure for the proposed methods for the correction of conservative type I error rates of SKAT family tests when the trait of interest is dichotomous and the sample size is small. Both small-sample-adjusted SKAT and the optimal unified test (SKAT-O) are computationally efficient and can easily be applied to genome-wide sequencing association studies. We evaluate the finite sample performance of the proposed methods using extensive simulation studies and illustrate their application using the acute-lung-injury exome-sequencing data of the National Heart, Lung, and Blood Institute Exome Sequencing Project.

SUBMITTER: Lee S

PROVIDER: S-EPMC3415556 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies.

Lee Seunggeun S Emond Mary J MJ Bamshad Michael J MJ Barnes Kathleen C KC Rieder Mark J MJ Nickerson Deborah A DA Christiani David C DC Wurfel Mark M MM Lin Xihong X

American journal of human genetics 20120802 2

We propose in this paper a unified approach for testing the association between rare variants and phenotypes in sequencing association studies. This approach maximizes power by adaptively using the data to optimally combine the burden test and the nonburden sequence kernel association test (SKAT). Burden tests are more powerful when most variants in a region are causal and the effects are in the same direction, whereas SKAT is more powerful when a large fraction of the variants in a region are n ...[more]

PMID: 22863193

Similar Datasets

Project description:Background:Extraordinary progress has been made in our understanding of common variants in many diseases, including melanoma. Because the contribution of rare coding variants is not as well characterized, we performed an exome-wide, gene-based association study of familial cutaneous melanoma (CM) and ocular melanoma (OM). Methods:Using 11?990 jointly processed individual DNA samples, whole-exome sequencing was performed, followed by large-scale joint variant calling using GATK (Genome Analysis ToolKit). PLINK/SEQ was used for statistical analysis of genetic variation. Four models were used to estimate the association among different types of variants. In vitro functional validation was performed using three human melanoma cell lines in 2D and 3D proliferation assays. In vivo tumor growth was assessed using xenografts of human melanoma A375 melanoma cells in nude mice (eight mice per group). All statistical tests were two-sided. Results:Strong signals were detected for CDKN2A (Pmin = 6.16?×?10-8) in the CM cohort (n?=?273) and BAP1 (Pmin = 3.83?×?10-6) in the OM (n?=?99) cohort. Eleven genes that exhibited borderline association (P < 10-4) were independently validated using The Cancer Genome Atlas melanoma cohort (379?CM, 47 OM) and a matched set of 3563 European controls with CDKN2A (P = .009), BAP1 (P = .03), and EBF3 (P = 4.75?×?10-4), a candidate risk locus, all showing evidence of replication. EBF3 was then evaluated using germline data from a set of 132 familial melanoma cases and 4769 controls of UK origin (joint P = 1.37?×?10-5). Somatically, loss of EBF3 expression correlated with progression, poorer outcome, and high MITF tumors. Functionally, induction of EBF3 in melanoma cells reduced cell growth in vitro, retarded tumor formation in vivo, and reduced MITF levels. Conclusions:The results of this large rare variant germline association study further define the mutational landscape of hereditary melanoma and implicate EBF3 as a possible CM predisposition gene.

Dataset Information

Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies.

Publications

Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets