partial_cor {INDEED}R Documentation

Data preprocessing for partial correlaton analysis

Description

A method that integrates differential expression (DE) analysis and differential network (DN) analysis to select biomarker candidates for survival time prediction. partial_cor is the second step of partial correlation calculation after the output result from pre_partial function

Usage

partial_cor(data_list = NULL, rho_group1 = NULL, rho_group2 = NULL,
  permutation = 1000, p_val = NULL)

Arguments

data_list,

list of pre-processed data from pre_partial function

rho_group1

rule to choose rho for group 1, "min": minimum rho, "ste" one standard error from minimum, or user can input rho of their choice, default: minimum

rho_group2

rule to choose rho for group 1, "min": minimum rho, "ste" one standard error from minimum, or user can input rho of their choice, default: minimum

permutation,

a positive integer of desired number of permutations, default 1000

p_val

optional, a dataframe contains p values for each metabolite/molecule

Value

a list containing a score dataframe and a differential network dataframe

Examples

preprocess<- pre_partial(data=Met_GU,class_label = Met_Group_GU,id=Met_name_GU)
   partial_cor(data_list=preprocess,rho_group1='min',
   rho_group2="min",permutation = 1000,p_val=pvalue_M_GU)

[Package INDEED version 1.0.1 Index]