GAPIT: genome association and prediction integrated tool.
CONCLUSIONS
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.


BACKGROUND
http://www.maizegenetics.net/GAPIT.


BACKGROUND
zhiwu.zhang@cornell.edu


BACKGROUND
Supplementary data are available at Bioinformatics online.
Computational Biologist with the United States Department of Agriculture - Agricultural Research Service, Ithaca, NY 14853, USA.
Alexander E
AE
Lipka
Feng
F
Tian
Qishan
Q
Wang
Jason
J
Peiffer
Meng
M
Li
Peter J
PJ
Bradbury
Michael A
MA
Gore
Edward S
ES
Buckler
Zhiwu
Z
Zhang
D055106:Genome-Wide Association Study; D023281:Genomics / Q000379:methods; D006801:Humans; D016014:Linear Models; D020641:Polymorphism, Single Nucleotide; D012984:Software