GAPIT, a Genome Association and Prediction Integrated Tool, was released to public in 2011 by Dr. Zhiwu Zhang when he worked in Edward Buckler Lab at Cornell University. With the base of EMMA algorithm, GAPIT package in R implemented state of art algorithms for Genome-Wide Association Study (GWAS) and genomic prediction, including Compressed Mixed Linear Model (CMLM). The corresponding paper was published at Bioinformatics (Lipka et al, 2012). Buckler Lab continues the hosting of GAPIT website after both the first author (Alex Lipka) and corresponding author (Zhiwu Zhang) joined the faculty at University of Illinois and Washing State University , respectively. This effort allows existing user to use the original links to access GAPIT.


The implemented GWAS methods include GLM, MLM, EMMAx/P3D, CMLM, ECMLM, FaST-LMM, SUPER, MLMM, and FarmCPU. The implemented GS methods include gBLUP, sBLUP, and cBLUP, which are superior for traits controlled by many genes, less genes and genes ex-plaining small fraction of phenotypic variation, respectively, and Interactive plot.


The most updated GAPIT documents can be download or accessed here: