Statistical analysis of rare sequence variants: An overview of collapsing methods

Carmen Dering, Claudia Hemmelmann, Elizabeth Pugh, Andreas Ziegler

Research output: Contribution to journalArticle

Abstract

With the advent of novel sequencing technologies, interest in the identification of rare variants that influence common traits has increased rapidly. Standard statistical methods, such as the Cochrane-Armitage trend test or logistic regression, fail in this setting for the analysis of unrelated subjects because of the rareness of the variants. Recently, various alternative approaches have been proposed that circumvent the rareness problem by collapsing rare variants in a defined genetic region or sets of regions. We provide an overview of these collapsing methods for association analysis and discuss the use of permutation approaches for significance testing of the data-adaptive methods. Genet.

Original languageEnglish (US)
Pages (from-to)S12-S17
JournalGenetic epidemiology
Volume35
Issue numberSUPPL. 1
DOIs
StatePublished - Dec 5 2011

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Keywords

  • Association
  • Collapsing methods
  • Collection of rare variants
  • Common disease/rare variant hypothesis
  • Contingency table
  • Generalized linear model
  • Next-generation sequencing
  • Pooling methods

ASJC Scopus subject areas

  • Epidemiology
  • Genetics(clinical)

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