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Title: Rare-variant association analysis: study designs and statistical tests.

Authors: Lee, Seunggeung; Abecasis, Gonçalo R; Boehnke, Michael; Lin, Xihong

Published In Am J Hum Genet, (2014 Jul 03)

Abstract: Despite the extensive discovery of trait- and disease-associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants can explain additional disease risk or trait variability. An increasing number of studies are underway to identify trait- and disease-associated rare variants. In this review, we provide an overview of statistical issues in rare-variant association studies with a focus on study designs and statistical tests. We present the design and analysis pipeline of rare-variant studies and review cost-effective sequencing designs and genotyping platforms. We compare various gene- or region-based association tests, including burden tests, variance-component tests, and combined omnibus tests, in terms of their assumptions and performance. Also discussed are the related topics of meta-analysis, population-stratification adjustment, genotype imputation, follow-up studies, and heritability due to rare variants. We provide guidelines for analysis and discuss some of the challenges inherent in these studies and future research directions.

PubMed ID: 24995866 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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