epiblaster1geno {episcan} | R Documentation |
Parallelized calculation of the difference of correlation coefficients and compute
test with one genotype input
Description
Calculate the difference of correlation coefficents between cases and controls,
conduct 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)