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

• Published in: Genetic epidemiology Vol. 35; no. S1; pp. S12 - S17
• Main Authors: Dering, Carmen, Hemmelmann, Claudia, Pugh, Elizabeth, Ziegler, Andreas
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 2011
• Subjects: association; Association analysis; collapsing methods; collection of rare variants; common disease/rare variant hypothesis; contingency table; generalized linear model; Genetic Predisposition to Disease; Humans; Models, Genetic; Models, Statistical; Molecular Epidemiology - methods; next-generation sequencing; pooling methods; Reviews; Sequence Analysis; Statistical analysis; Statistics
• ISSN: 0741-0395; 1098-2272; 1098-2272
• DOI: 10.1002/gepi.20643

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. Epidemiol. 35:S12–S17, 2011. © 2011 Wiley Periodicals, Inc.