non_partial_cor {INDEED} | R Documentation |
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
non_partial_cor(data = NULL, class_label = NULL, id = NULL, method = "pearson", p_val = NULL, permutation = 1000)
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 |
a list of processed data for next step and rho
non_partial_cor(data=Met_GU,class_label = Met_Group_GU,id=Met_name_GU, method="spearman")