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Statistical analysis of rare sequence variants: an overview of collapsing methods
Author(s) -
Dering Carmen,
Hemmelmann Claudia,
Pugh Elizabeth,
Ziegler Andreas
Publication year - 2011
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20643
Subject(s) - permutation (music) , identification (biology) , significance testing , sequence (biology) , computational biology , association test , logistic regression , statistical analysis , statistical hypothesis testing , biology , statistics , computer science , evolutionary biology , genetics , mathematics , genotype , single nucleotide polymorphism , gene , botany , physics , acoustics
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. Epidemiol . 35:S12–S17, 2011. © 2011 Wiley Periodicals, Inc.