permutation_cor: Permutations to build a differential network based on...

In INDEED: Interactive Visualization of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection Package

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 statistically significant if it falls into the 2.5 empirical distribution curve.

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 containing group 1 data.
data_group_2	THis is a n*p matrix containing group 2 data.
type_of_cor	If this is NULL, pearson correlation coefficient will be calculated as default. Otherwise, a character string "spearman" will calculate the spearman correlation coefficient.

Value

A multi-dimensional matrix that contains the permutation result.

INDEED documentation built on Nov. 8, 2020, 11:12 p.m.