rMVP: Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS Tool

A memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can (1) effectively process large data, (2) rapidly evaluate population structure, (3) efficiently estimate variance components several algorithms, (4) implement parallel-accelerated association tests of markers three methods, (5) globally efficient design on GWAS process computing, (6) enhance visualization of related information. 'rMVP' contains three models GLM (Alkes Price (2006) <doi:10.1038/ng1847>), MLM (Jianming Yu (2006) <doi:10.1038/ng1702>) and FarmCPU (Xiaolei Liu (2016) <doi:10.1371/journal.pgen.1005767>); variance components estimation methods EMMAX (Hyunmin Kang (2008) <doi:10.1534/genetics.107.080101>;), FaSTLMM (method: Christoph Lippert (2011) <doi:10.1038/nmeth.1681>, R implementation from 'GAPIT2': You Tang and Xiaolei Liu (2016) <doi:10.1371/journal.pone.0107684> and 'SUPER': Qishan Wang and Feng Tian (2014) <doi:10.1371/journal.pone.0107684>), and HE regression (Xiang Zhou (2017) <doi:10.1214/17-AOAS1052>).

Version: 1.3.0
Depends: R (≥ 3.3)
Imports: utils, stats, methods, graphics, grDevices, MASS, bigmemory, RhpcBLASctl
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppProgress, BH, bigmemory
Suggests: knitr, testthat, rmarkdown
Published: 2024-12-17
DOI: 10.32614/CRAN.package.rMVP
Author: Lilin Yin [aut], Haohao Zhang [aut], Zhenshuang Tang [aut], Jingya Xu [aut], Dong Yin [aut], Zhiwu Zhang [aut], Xiaohui Yuan [aut], Mengjin Zhu [aut], Shuhong Zhao [aut], Xinyun Li [aut], Qishan Wang [ctb], Feng Tian [ctb], Hyunmin Kang [ctb], Xiang Zhou [ctb], Xiaolei Liu [cre, aut, cph]
Maintainer: Xiaolei Liu <xll198708 at gmail.com>
BugReports: https://github.com/xiaolei-lab/rMVP/issues
License: Apache License 2.0
URL: https://github.com/xiaolei-lab/rMVP
NeedsCompilation: yes
Materials: ChangeLog
In views: Agriculture
CRAN checks: rMVP results

Documentation:

Reference manual: rMVP.pdf

Downloads:

Package source: rMVP_1.3.0.tar.gz
Windows binaries: r-devel: rMVP_1.3.0.zip, r-release: rMVP_1.1.1.zip, r-oldrel: rMVP_1.3.0.zip
macOS binaries: r-release (arm64): rMVP_1.3.0.tgz, r-oldrel (arm64): rMVP_1.3.0.tgz, r-release (x86_64): rMVP_1.3.0.tgz, r-oldrel (x86_64): rMVP_1.3.0.tgz
Old sources: rMVP archive

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