epiblaster1geno: Parallelized calculation of the difference of correlation...

In episcan: Scan Pairwise Epistasis

Description

Calculate the difference of correlation coefficents between cases and controls, conduct Z test for the differences (values) and choose variant pairs with the significance below the given threshold for output.

Usage

epiblaster1geno(geno, pheno, chunk = 1000, zpthres = 1e-05,
  outfile = "NONE", suffix = ".txt", ...)

Arguments

geno	is the normalized genotype data. It can be a matrix or a dataframe, or a big.matrix object (from bigmemory. The columns contain the information of variables and the rows contain the information of samples.
pheno	a vector containing the binary phenotype information (case/control). The values are either 0 (control) or 1 (case).
chunk	is the number of variants in each chunk. Default: 1000.
zpthres	is the significance threshold to select variant pairs for output. Default is 1e-6.
outfile	is the base of out filename. Default: 'NONE'.
suffix	is the suffix of out filename. Default: '.txt'.
...	not used.

Value

null

Examples

# simulate some data
set.seed(123)
geno1 <- matrix(sample(0:2, size = 1000, replace = TRUE, prob = c(0.5, 0.3, 0.2)), ncol = 10)
dimnames(geno1) <- list(row = paste0("IND", 1:nrow(geno1)), col = paste0("rs", 1:ncol(geno1)))
p1 <- c(rep(0, 60), rep(1, 40))

# normalized data
geno1 <- scale(geno1)

# one genotype with case-control phenotype
epiblaster1geno(geno = geno1, 
pheno = p1,
outfile = "episcan_1geno_cc", 
suffix = ".txt", 
zpthres = 0.9, 
chunk = 10)

# take a look at the result
res <- read.table("episcan_1geno_cc.txt", 
header = TRUE, 
stringsAsFactors = FALSE)
head(res)

episcan documentation built on May 2, 2019, 9:42 a.m.