title: Identifying rare variants associated with complex traits via sequencing.
abstract: Although genome-wide association studies have been successful in detecting associations with common variants, there is currently an increasing interest in identifying low-frequency and rare variants associated with complex traits. Next-generation sequencing technologies make it feasible to survey the full spectrum of genetic variation in coding regions or the entire genome. The association analysis for rare variants is challenging, and traditional methods are ineffective, however, due to the low frequency of rare variants, coupled with allelic heterogeneity. Recently a battery of new statistical methods has been proposed for identifying rare variants associated with complex traits. These methods test for associations by aggregating multiple rare variants across a gene or a genomic region or among a group of variants in the genome. In this unit, we describe key concepts for rare variant association for complex traits, survey some of the recent methods, discuss their statistical power under various scenarios, and provide practical guidance on analyzing next-generation sequencing data for identifying rare variants associated with complex traits.
authors.affiliation: Department of Molecular Physiology and Biophysics, Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Bingshan
authors.initials: B
authors.lastname: Li
authors.forename: Dajiang J
authors.initials: DJ
authors.lastname: Liu
authors.forename: Suzanne M
authors.initials: SM
authors.lastname: Leal
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D014644:Genetic Variation; D055106:Genome-Wide Association Study; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D020412:Multifactorial Inheritance; D019655:Quantitative Trait, Heritable