episcan (version 0.0.1)

epiHSIC1geno: Calculate epistasis using HSIC with one genotype input

Description

Calculate the significance of epistasis according the definition of HSIC, conduct \(Z\) 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

Examples

# NOT RUN {
# 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)
# }