permutation_pc: Permutations to build differential network using partial...

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 paired partial correlation is considered significant if it falls into the 2.5 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	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.
rho_group_1_opt	optimal tuning parameter to sparse the differential network for group 1
rho_group_2_opt	optimal tuning parameter to sparse the differential network for group 2

Value

A multi-dimensional matrix that contains the permutation results

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