permutation_pc: Permutations to build differential network based on partial...

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 paired partial correlation is considered statistically significant if it falls into the 2.5 empirical distribution curve.

Usage

permutation_pc(m, p, n_group_1, n_group_2, data_group_1, data_group_2,
  rho_group_1_opt, rho_group_2_opt)

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.
rho_group_1_opt	This is an optimal tuning parameter to obtain a sparse differential network for group 1.
rho_group_2_opt	This is an optimal tuning parameter to obtain a sparse differential network for group 2.

Value

A multi-dimensional matrix that contains the permutation result.

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