Nothing
library("MatrixEQTL")
# Number of samples
n = 100;
# Number of variables
ngs = 2000;
# Common signal in all variables (population stratification)
pop = 0.2 * rnorm(n);
# data matrices
snps.mat = matrix(rnorm(n*ngs), ncol = ngs) + pop;
gene.mat = matrix(rnorm(n*ngs), ncol = ngs) + pop + snps.mat*((1:ngs)/ngs)^9/2;
# data objects for Matrix eQTL engine
snps1 = SlicedData$new( t( snps.mat ) );
gene1 = SlicedData$new( t( gene.mat ) );
cvrt1 = SlicedData$new();
rm(snps.mat, gene.mat);
# Slice data in blocks of 500 variables
snps1$ResliceCombined(500);
gene1$ResliceCombined(500);
# Perform analysis recording information for a histogram
me = Matrix_eQTL_main(
snps = snps1,
gene = gene1,
cvrt = cvrt1,
output_file_name = NULL,
pvOutputThreshold = 1e-100,
useModel = modelLINEAR,
errorCovariance = numeric(),
verbose = TRUE,
pvalue.hist = 100);
# png(filename = "histogram.png", width = 650, height = 650);
plot(me, col="grey");
# dev.off();
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