GAPIT: genome association and prediction integrated tool

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ID: 290905
2012
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Abstract
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.
Reference Key
openalex_W2161620511 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Alexander E. Lipka, Feng Tian, Qishan Wang, Jason A. Peiffer, Meng Li, Peter J. Bradbury, Michael A. Gore, Edward S. Buckler, Zhiwu Zhang
Journal BMC Bioinformatics
Year 2012
DOI
10.1093/bioinformatics/bts444
URL
https://academic.oup.com/bioinformatics/article-pdf/28/18/2397/48881198/bioinformatics_28_18_2397.pdf
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