epiHSIC1geno {episcan} | R Documentation |
Calculate epistasis using HSIC with one genotype input
Description
Calculate the significance of epistasis according the definition of HSIC, conduct test for HSIC values and
choose variant pairs with the significance below the given threshold for output.
Usage
epiHSIC1geno(geno = NULL, 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 |
is a vector containing the normalized phenotype information. |
chunk |
is the number of variants in each chunk. |
zpthres |
is is the significance threshold to select variant pairs for output. Default is 1e-6. |
outfile |
is the basename of out filename. |
suffix |
is the suffix of out filename. |
... |
not used. |
Value
null
Author(s)
Beibei Jiang beibei_jiang@psych.mpg.de
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)))
p2 <- rnorm(100, mean = 5, sd = 10)
# normalized data
geno1 <- scale(geno1)
p2 <- as.vector(unlist(scale(p2)))
# one genotypes with quantitative phenotype
epiHSIC1geno(geno = geno1,
pheno = p2,
outfile = "episcan_1geno_quant",
suffix = ".txt",
zpthres = 0.9,
chunk = 10)
# take a look at the result
res <- read.table("episcan_1geno_quant.txt",
header = TRUE,
stringsAsFactors = FALSE)
head(res)
[Package episcan version 0.0.1 Index]