IGG3: a tool to rapidly integrate large genotype datasets for whole-genome imputation and individual-level meta-analysis

被引：10

作者：

Li, Miao-Xin ^{[1
]}

Jiang, Lin ^{[2
]}

Kao, Patrick Yu-Ping ^{[1
]}

Sham, Pak-C. ^{[3
,4
]}

Song, You-Qiang ^{[1
,3
]}

机构：

[1] Univ Hong Kong, Dept Biochem, Pokfulam, Hong Kong, Peoples R China

[2] Hunan Univ Commerce, Ctr Expt, Changsha 410205, Hunan, Peoples R China

[3] Univ Hong Kong, Ctr Reprod Dev & Growth, Pokfulam, Hong Kong, Peoples R China

[4] Univ Hong Kong, Dept Psychiat, Pokfulam, Hong Kong, Peoples R China

来源：

BIOINFORMATICS | 2009年 / 25卷 / 11期

关键词：

WIDE ASSOCIATION;

D O I：

10.1093/bioinformatics/btp183

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

There is an urgent and increasing demand for integrating large genotype datasets across genome-wide association studies and HapMap project for whole-genome imputation and individual-level meta-analysis. A new algorithm was developed to efficiently merge raw genotypes across large datasets and implemented in the latest version of IGG, IGG3. In addition, IGG3 can integrate the latest phased and unphased HapMap genotypes and can flexibly generate complete sets of input files for six popular genotype imputation tools. We demonstrated the efficiency of IGG3 by simulation tests, which could rapidly merge genotypes in tens of thousands of large genotype chips (e.g. Affymetrix Genome-Wide Human SNP Array 6.0 and Illumina Human1m- duo) and in HapMap III project on an ordinary desktop computer.

引用

页码：1449 / 1450

页数：2

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