Abstract
ABSTRACTThe advent of large-scale genetic studies has helped bring a new era of biomedical research on dissecting the genetic architecture of complex human disease. Genome-wide association studies (GWASs) and next-generation sequencing studies are two popular tools for identifying genetic variants that are associated with complex traits. This article overviews some of the most important statistical tools for analyzing data from these two types of studies, with an emphasis on single-SNP tests for common variants and region-based tests for rare variants. We compare various statistical methods for common and rare variants in humans, and describe some critical considerations to guide the choice of an analysis method. Also discussed are the related topics of sample ascertainment, missing heritability, and multiple testing correction, as well as some remaining analytical challenges presented by complex trait association mapping using genomic data obtained via high-throughput technologies.
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