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 (doi:10.1038/ng1847), MLM (doi:10.1038/ng1702) and FarmCPU (doi:10.1371/journal.pgen.1005767); variance components estimation methods EMMAX (doi:10.1534/genetics.107.080101;), FaSTLMM (doi:10.1038/nmeth.1681, R implementation from 'GAPIT2': doi:10.1371/journal.pone.0107684 and 'SUPER': doi:10.1371/journal.pone.0107684), and HE regression (doi:10.1214/17-AOAS1052).
- Version1.4.0
- R versionR (≥ 3.3)
- LicenseApache License 2.0
- Needs compilation?Yes
- Last release01/22/2025
Documentation
Team
Xiaolei Liu
MaintainerShow author detailsJingya Xu
Show author detailsRolesAuthorDong Yin
Show author detailsRolesAuthorQishan Wang
Show author detailsRolesContributorFeng Tian
Show author detailsRolesContributorShuhong Zhao
Show author detailsRolesAuthorXiang Zhou
Show author detailsRolesContributorXinyun Li
Show author detailsRolesAuthorLilin Yin
Show author detailsRolesAuthorMengjin Zhu
Show author detailsRolesAuthorZhenshuang Tang
Show author detailsRolesAuthorXiaohui Yuan
Show author detailsRolesAuthorHyunmin Kang
Show author detailsRolesContributorZhiwu Zhang
Show author detailsRolesAuthorHaohao Zhang
Show author detailsRolesAuthor
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- Imports3 packages
- Suggests3 packages
- Linking To6 packages