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rMVP  

Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS Tool
View on CRAN: Click here


Download and install rMVP package within the R console
Install from CRAN:
install.packages("rMVP")

Install from Github:
library("remotes")
install_github("cran/rMVP")

Install by package version:
library("remotes")
install_version("rMVP", "1.0.8")



Attach the package and use:
library("rMVP")
Maintained by
Xiaolei Liu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-30
Latest Update: 2023-09-01
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>).
How to cite:
Xiaolei Liu (2019). rMVP: Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS Tool. R package version 1.0.8, https://cran.r-project.org/web/packages/rMVP
Previous versions and publish date:
0.99.15 (2019-08-30 09:30), 0.99.16 (2019-09-24 12:10), 0.99.17 (2019-10-18 15:10), 0.99.18 (2020-03-19 19:00), 1.0.0 (2020-05-07 17:10), 1.0.3 (2020-07-17 10:30), 1.0.4 (2020-09-01 14:30), 1.0.5 (2021-03-02 16:40), 1.0.6 (2021-04-18 16:50), 1.0.7 (2023-09-01 10:30)
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