GAPIT: genome association and prediction integrated tool

被引：1621

作者：

Lipka, Alexander E. ^{[2
]}

Tian, Feng ^{[1
]}

Wang, Qishan ^{[3
]}

Peiffer, Jason ^{[4
]}

Li, Meng ^{[1
,5
]}

Bradbury, Peter J. ^{[2
]}

Gore, Michael A. ^{[6
]}

Buckler, Edward S. ^{[1
,2
,4
]}

Zhang, Zhiwu ^{[1
]}

机构：

[1] Cornell Univ, Inst Genom Divers, Ithaca, NY 14853 USA

[2] ARS, USDA, Ithaca, NY 14853 USA

[3] Shanghai Jiao Tong Univ, Dept Anim Sci, Shanghai 200240, Peoples R China

[4] Cornell Univ, Dept Plant Breeding & Genet, Ithaca, NY 14853 USA

[5] Nanjing Agr Univ, Ctr Pear Engn Technol Res, Nanjing 210095, Jiangsu, Peoples R China

[6] ARS, US Arid Land Agr Res Ctr, USDA, Maricopa, AZ 85138 USA

来源：

BIOINFORMATICS | 2012年 / 28卷 / 18期

基金：

美国农业部; 美国国家科学基金会;

关键词：

WIDE ASSOCIATION; MODEL; SAMPLES;

D O I：

10.1093/bioinformatics/bts444

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results.

引用

页码：2397 / 2399

页数：3

共 15 条

[1] CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].