Package: rMVP
Type: Package
Title: Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS
        Tool
Version: 1.4.6
Date: 2026-03-10
Authors@R: c( person("Lilin", "Yin", role = "aut"), 
              person("Haohao", "Zhang", role = "aut"),
              person("Zhenshuang", "Tang", role = "aut"),
              person("Jingya", "Xu", role = "aut"),
              person("Dong", "Yin", role = "aut"),
              person("Zhiwu", "Zhang", role = "aut"),
              person("Xiaohui", "Yuan", role = "aut"),
              person("Mengjin", "Zhu", role = "aut"),
              person("Shuhong", "Zhao", role = "aut"),
              person("Xinyun", "Li", role = "aut"),
              person("Qishan", "Wang", role = "ctb"),
              person("Feng", "Tian", role = "ctb"),
              person("Hyunmin", "Kang", role = "ctb"),
              person("Xiang", "Zhou", role = "ctb"),
              person("Xiaolei", "Liu", role = c("cre", "aut", "cph"), email = "xll198708@gmail.com"))
Description: 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>).
License: Apache License 2.0
Encoding: UTF-8
URL: https://github.com/xiaolei-lab/rMVP
BugReports: https://github.com/xiaolei-lab/rMVP/issues
Imports: utils, stats, methods, graphics, grDevices, MASS, bigmemory,
        RhpcBLASctl
Depends: R (>= 3.3)
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppProgress, BH, bigmemory
NeedsCompilation: yes
Suggests: knitr, testthat, rmarkdown
RoxygenNote: 7.3.3
Maintainer: Xiaolei Liu <xll198708@gmail.com>
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]
Repository: https://xiaolei-lab.r-universe.dev
Date/Publication: 2026-05-27 12:31:58 UTC
RemoteUrl: https://github.com/xiaolei-lab/rmvp
RemoteRef: HEAD
RemoteSha: 78fc9e636439c3b5171ee05d0460e3ad4df3129a
Packaged: 2026-07-04 07:55:44 UTC; root