GWAS and Genomic Selection in R Using the Genome Association and Prediction Integrated Tool (GAPIT) Package.

Advances in high throughput sequencing have improved the detection of genes underlying important traits as well as the prediction accuracy of disease risk and breeding value of crop or livestock. Software programs developed to perform statistical genetic analysis that support these activities should maximize statistical power in genome-wide association studies, provide high accuracy in genomic prediction and selection, and run in a computationally efficient manner. To address these challenges, we developed an R package called Genomic Association and Prediction Integrated Tool (GAPIT). This package implements advanced statistical methods that have been developed over the past ten years, including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large data sets in excess of over ten thousand individuals and one million SNPs using approaches that maximize statistical power, while at the same time providing user-friendly access and high quality result graphics. The GAPIT R package is freely available to the public at www.maizegenetics.net/GAPIT.