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

被引:70
作者
Dering, Carmen [1 ]
Hemmelmann, Claudia [1 ]
Pugh, Elizabeth [2 ]
Ziegler, Andreas [1 ]
机构
[1] Univ Lubeck, Univ Klinikum Schleswig Holstein, Inst Med Biometrie & Stat, D-23562 Lubeck, Germany
[2] Johns Hopkins Univ, Sch Med, Ctr Inherited Dis Res, Baltimore, MD USA
基金
美国国家卫生研究院;
关键词
association; collapsing methods; collection of rare variants; common disease; rare variant hypothesis; contingency table; generalized linear model; next-generation sequencing; pooling methods; MISSING HERITABILITY; COMMON DISEASES; ASSOCIATION; STRATEGIES; HAPLOTYPE; MUTATIONS; GENOMES; RISK; GENE;
D O I
10.1002/gepi.20643
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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:S12S17, 2011. (C) 2011 Wiley Periodicals, Inc.
引用
收藏
页码:S12 / S17
页数:6
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