permut: Permutation test when 'dist_permutations' is specified
In ccdf: Distribution-Free Single-Cell Differential Expression Analysis

Description Usage Arguments Value Examples

View source: R/permut.R

Permutation test when dist_permutations is specified

permut(
  Y,
  X,
  Z = NULL,
  distance = "L2",
  n_perm,
  method = "logistic regression",
  parallel = TRUE,
  n_cpus = NULL,
  fast = TRUE
)

`Y`	a numeric vector of size `n` containing the preprocessed expressions from `n` samples (or cells).
`X`	a data frame containing numeric or factor vector(s) of size `n` containing the variable(s) to be tested (the condition(s) to be tested).
`Z`	a data frame containing numeric or factor vector(s) of size `n` containing the covariate(s).
`method`	a character string indicating which method to use to compute the CCDF, either `'linear regression'`, `'logistic regression'` and `'permutations'` or `'RF'` for Random Forests. Default is `'linear regression'` since it is the method used in the test. #'@param 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`.
`fast`	a logical flag indicating whether the fast implementation of logistic regression should be used. Only if `'dist_permutations'` is specified. Default is `TRUE`.

A data frame with the following elements:

score contains the test statistic for a given gene.
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))
permut(Y,X,method="linear regression",n_perm=10,n_cpus=2)}