GAPIT: genome association and prediction integrated tool

Bioinformatics. 2012 Sep 15;28(18):2397-9. doi: 10.1093/bioinformatics/bts444. Epub 2012 Jul 13.


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.



Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Genome-Wide Association Study*
  • Genomics / methods
  • Humans
  • Linear Models
  • Polymorphism, Single Nucleotide*
  • Software*