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

Description Usage Arguments Value

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. This function is used in partial_corr.R

Usage

1
2
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 or data.frame containing group 1 data.

data_group_2

This is a n*p matrix of data.frame containing group 2 data.

rho_group_1_opt

This is an optimal tuning parameter to sparse the differential network for group 1

rho_group_2_opt

This is an optimal tuning parameter to sparse the differential network for group 2

Value

A multi-dimensional matrix that contains the permutation results


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