permutation_cor: Permutations to build differential network using correlation

In cx30/INDEED: An Implementation of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection

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.

Usage

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

Arguments

m	number of permutations.
p	number of biomarker candidates.
n_group_1	number of subjects in group 1.
n_group_2	number of subjects in group 2.
data_group_1	a n*p matrix or data.frame containing group 1 data.
data_group_2	a n*p matrix of data.frame containing group 2 data.
type_of_cor	if NULL, pearson correlation coefficient will be calculated. Otherwise, a character string "spearman" to calculate spearman correlation coefficient.

Value

A multi-dimensional matrix that contains the permutation results

cx30/INDEED documentation built on May 5, 2019, 2:41 a.m.