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


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Documentation for package ‘INDEED’ version 2.19.0

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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