Identifying rare variants associated with complex traits via sequencing

Bingshan Li, Dajiang Liu, Suzanne M. Leal

Research output: Contribution to journalArticle

20 Citations (Scopus)

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.

Original languageEnglish (US)
Article number1.26
JournalCurrent protocols in human genetics
Issue numberSUPPL.78
DOIs
StatePublished - Jan 1 2013

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Genome
Genome-Wide Association Study
Technology
Genes
Surveys and Questionnaires

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

Cite this

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Identifying rare variants associated with complex traits via sequencing. / Li, Bingshan; Liu, Dajiang; Leal, Suzanne M.

In: Current protocols in human genetics, No. SUPPL.78, 1.26, 01.01.2013.

Research output: Contribution to journalArticle

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