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. partial_cor is the second step of partial correlation calculation after the output result from pre_partial function
partial_cor(data_list = NULL, rho_group1 = NULL, rho_group2 = NULL, permutation = 1000, p_val = NULL)
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 |
a list containing a score dataframe and a differential network dataframe
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)