RMVP: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated Tool for Genome-wide Association Study.

ABSTRACT: Along with the development of high-throughput sequencing technologies, both sample size and SNP number are increasing rapidly in genome-wide association studies (GWAS), and the associated computation is more challenging than ever. Here, we present a memory-efficient, visualization-enhanced, and parallel-accelerated R package called "rMVP" to address the need for improved GWAS computation. rMVP can 1) effectively process large GWAS data, 2) rapidly evaluate population structure, 3) efficiently estimate variance components by Efficient Mixed-Model Association eXpedited (EMMAX), Factored Spectrally Transformed Linear Mixed Models (FaST-LMM), and Haseman-Elston (HE) regression algorithms, 4) implement parallel-accelerated association tests of markers using general linear model (GLM), mixed lin

SUBMITTER: Yin L 

PROVIDER: S-EPMC9040015 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature