Genotype imputation for genome-wide association studies

被引:1107
|
作者
Marchini, Jonathan [1 ]
Howie, Bryan [2 ]
机构
[1] Univ Oxford, Dept Stat, Oxford OX1 3TG, England
[2] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA
基金
美国国家科学基金会; 英国医学研究理事会;
关键词
HAPLOTYPE-PHASE INFERENCE; HIDDEN MARKOV-MODELS; SUSCEPTIBILITY LOCI; MULTIPLE-SCLEROSIS; STATISTICAL-METHOD; HLA ALLELES; METAANALYSIS; ACCURACY; REPLICATION; RISK;
D O I
10.1038/nrg2796
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
In the past few years genome-wide association (GWA) studies have uncovered a large number of convincingly replicated associations for many complex human diseases. Genotype imputation has been used widely in the analysis of GWA studies to boost power, fine-map associations and facilitate the combination of results across studies using meta-analysis. This Review describes the details of several different statistical methods for imputing genotypes, illustrates and discusses the factors that influence imputation performance, and reviews methods that can be used to assess imputation performance and test association at imputed SNPs.
引用
收藏
页码:499 / 511
页数:13
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