MVP.GLM {rMVP} | R Documentation |
Build date: Aug 30, 2016 Last update: May 25, 2017
MVP.GLM(phe, geno, CV = NULL, cpu = 1, bar = TRUE, verbose = TRUE)
phe |
phenotype, n * 2 matrix |
geno |
Genotype in numeric format, pure 0, 1, 2 matrix; m * n, m is marker size, n is population size |
CV |
Covariance, design matrix(n * x) for the fixed effects |
cpu |
number of cpus used for parallel computation |
bar |
whether to show the progress bar |
verbose |
whether to print detail. |
m * 2 matrix, the first column is the SNP effect, the second column is the P values
Lilin Yin and Xiaolei Liu
phePath <- system.file("extdata", "07_other", "mvp.phe", package = "rMVP") phenotype <- read.table(phePath, header=TRUE) idx <- !is.na(phenotype[, 2]) phenotype <- phenotype[idx, ] print(dim(phenotype)) genoPath <- system.file("extdata", "06_mvp-impute", "mvp.imp.geno.desc", package = "rMVP") genotype <- attach.big.matrix(genoPath) genotype <- genotype[, idx] print(dim(genotype)) glm <- MVP.GLM(phe=phenotype, geno=genotype) str(glm)