non_partial_cor {INDEED}R Documentation

Non-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. non_partial_cor is a one step function for user to perform analysis, no pre-processing step required

Usage

non_partial_cor(data = NULL, class_label = NULL, id = NULL,
  method = "pearson", p_val = NULL, permutation = 1000)

Arguments

data,

input matrix of expression from all metabolites from all samples

class_label,

a binary array with 0: group 1; 1: group 2.

id,

an array of biomolecule ID to label.

method

a character string indicating which correlation coefficient is to be computed. One of "pearson" (default) or "spearman".

p_val

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

permutation,

a positive integer of desired number of permutations, default 1000

Value

a list of processed data for next step and rho

Examples

non_partial_cor(data=Met_GU,class_label = Met_Group_GU,id=Met_name_GU,
   method="spearman")

[Package INDEED version 1.0.1 Index]