permutation_cor: Permutations to build a differential network using...

In kg737/INDEED_Patch: Integrated Differential Expression and Differential Network Analysis (INDEED)

Description

A permutation test that randomly permutes the sample labels in distinct biological groups for each biomolecule. The difference in each paired biomolecule is considered significant if it falls into the 2.5 distribution curve. This function is used in non_partial_corr.R

Usage

permutation_cor(m, p, n_group_1, n_group_2, data_group_1, data_group_2,
  type_of_cor)

Arguments

m	This is the number of permutations desired.
p	This is the number of biomarker candidates present.
n_group_1	This is the number of subjects in group 1.
n_group_2	This is the number of subjects in group 2.
data_group_1	This is a n*p matrix or data.frame containing group 1 data.
data_group_2	This is a n*p matrix of data.frame containing group 2 data.
type_of_cor	If this is NULL, pearson correlation coefficient will be calculated by default. Otherwise, a character string "spearman" will calculate the spearman correlation coefficient.

Value

A multi-dimensional matrix that contains the permutation results

kg737/INDEED_Patch documentation built on May 22, 2019, 6:32 p.m.