MatrixEpistasis_main: matrixEpistasis

In fanglab/MatrixEpistasis: An ultrafast exhaustive epistasis scan for quantitative traits with covariate adjustment

Description

matrixEpistasis uses large matrix operation to perform the exhaustive epistasis scan for quantitative traits with covariate adjustment

Usage

MatrixEpistasis_main(snpA, snpB, trait, covariate = NULL,
  pvalThreshold = 1e-05, outputFileName)

Arguments

snpA	a matrix of numeric values in size of sample*snp representing the 1st group of SNPs, where the column names are the snp_ids
snpB	a matrix of numeric values in size of sample*snp representing the 2nd group of SNPs, where the column names are the snp_ids
trait	a vector of numeric values representing the quantitative trait
covariate	a matrix of numeric values in size of sample*covariate, by default, NULL
pvalThreshold	a numeric value representing the p-value threshold for matrixEpistasis output
outputFileName	a character value indicating the file name of matrixEpistasis output

Author(s)

Shijia Zhu, [e-mail]

See Also

matrixEpistasis; matrixPval; p2c;

Examples

# randomly generate a SNP matrix
snp <- sapply(1:100,function(i) rnorm(1000) )
# assign names to SNPs
colnames(snp) <- paste0('snp',1:100)
snpA = snp
snpB = snp
# radnomly generate a quantitative trait by simulating the relationship between SNPs and traits
trait <- snp %*% rnorm(100)
# use the top 5 PCs as the covariates 
covariate <- prcomp(snp)$x[,1:5]

MatrixEpistasis_main( snpA=snpA, snpB=snpB, trait=trait, covariate=covariate, pvalThreshold=1e-5, outputFileName='matrixEpistasis_pval_1e-5.txt')

fanglab/MatrixEpistasis documentation built on May 25, 2019, 5:22 p.m.