test_perm: Permutation test
In ccdf: Distribution-Free Single-Cell Differential Expression Analysis

Description Usage Arguments Value Examples

View source: R/test_perm.R

Permutation test

test_perm(
  Y,
  X,
  Z = NULL,
  n_perm = 100,
  parallel = FALSE,
  n_cpus = NULL,
  space_y = FALSE,
  number_y = length(Y)
)

`Y`	a numeric vector of size `n` containing the preprocessed expression for a given gene from `n` samples (or cells).
`X`	a data frame of numeric or factor vector(s) of size `n` containing the variable(s) to be tested (the condition(s)). Multiple variables are not allowed.
`Z`	a data frame of numeric or factor vector(s) of size `n` containing the covariate(s). Multiple variables are not allowed.
`n_perm`	the number of permutations. Default is `100`.
`parallel`	a logical flag indicating whether parallel computation should be enabled. Default is `TRUE`.
`n_cpus`	an integer indicating the number of cores to be used when `parallel` is `TRUE`. Default is `parallel::detectCores() - 1`.
`space_y`	a logical flag indicating whether the y thresholds are spaced. When `space_y` is `TRUE`, a regular sequence between the minimum and the maximum of the observations is used. Default is `FALSE`.
`number_y`	an integer value indicating the number of y thresholds (and therefore the number of regressions) to perform the test. Default is `length(Y)`.

A data frame with the following elements:

score contains the test statistic for a given gene.
raw_pval contains the raw p-values for a given gene computed from n_perm permutations.

if(interactive()){
X <- as.factor(rbinom(n=100, size = 1, prob = 0.5))
Y <- ((X==1)*rnorm(n = 50,0,1)) + ((X==0)*rnorm(n = 50,0.5,1))
res_perm <- test_perm(Y,data.frame(X=X),n_perm=10)}