GAPIT: genome association and prediction integrated tool
Bioinformatics, 2012•academic.oup.com
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 …
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 …
Abstract
Summary: 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.
Availability: http://www.maizegenetics.net/GAPIT.
Contact: zhiwu.zhang@cornell.edu
Supplementary Information: Supplementary data are available at Bioinformatics online.
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