Interactive Visualization of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection Package

Documentation for package ‘INDEED’ version 2.6.0

INDEED-package	INDEED: A network-based method for cacner biomarker discovery.
choose_rho	Draw error curve
compute_cor	Compute the correlation
compute_dns	Calculate the differential network score
compute_par	Compute the partial correlation
INDEED	INDEED: A network-based method for cacner biomarker discovery.
loglik_ave	Create log likelihood error
Met_Group_GU	Group label.
Met_GU	GU cirrhosis (CIRR) and GU Hepatocellular carcinoma (HCC) data.
Met_name_GU	KEGG ID
network_display	Interactive Network Visualization
non_partial_cor	Non-partial correlaton analysis
partial_cor	Partial correlaton analysis
permutation_cor	Permutations to build a differential network based on correlation analysis
permutation_pc	Permutations to build differential network based on partial correlation analysis
permutation_thres	Calculate the positive and negative thresholds based on the permutation result
pvalue_logit	Obtain p-values using logistic regression
pvalue_M_GU	P-values obtained by differential expression (DE) analysis.
scale_range	Scale list of numbers
select_rho_partial	Data preprocessing for partial correlaton analysis