Detecting multiple causal rare variants in exome sequence data

Kenny Q. Ye, Corinne D. Engelman

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Recent advances in sequencing technology have presented both opportunities and challenges, with limited statistical power to detect a single causal rare variant with practical sample sizes. To overcome this, the contributors to Group 1 of Genetic Analysis Workshop 17 sought to develop methods to detect the combined signal of multiple causal rare variants in a biologically meaningful way. The contributors used genes, genome location proximity, or genetic pathways as the basic unit in combining the information from multiple variants. Weaknesses of the exome sequence data and the relative strengths and weaknesses of the five approaches are discussed.

Original languageEnglish (US)
Pages (from-to)S18-S21
JournalGenetic Epidemiology
Volume35
Issue numberSUPPL. 1
DOIs
StatePublished - Dec 5 2011

Keywords

  • Bayesian
  • Pathways
  • Simulated

ASJC Scopus subject areas

  • Epidemiology
  • Genetics(clinical)

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