ressomlab/INDEED: Interactive Visualization of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection

An R package for integrated differential expression and differential network analysis based on omic data for cancer biomarker discovery. Both correlation and partial correlation can be used to generate differential network to aid the traditional differential expression analysis to identify changes between biomolecules on both their expression and pairwise association levels. A detailed description of the methodology has been published in Methods journal (PMID: 27592383). An interactive visualization feature allows for the exploration and selection of candidate biomarkers.

Getting started

Package details

AuthorYiming Zuo <>, Kian Ghaffari <>
Bioconductor views BiologicalQuestion DifferentialExpression ImmunoOncology MassSpectrometry Metabolomics ResearchField Software StatisticalMethod
MaintainerYiming Zuo <>, Habtom Ressom <>
LicenseMIT + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
ressomlab/INDEED documentation built on Aug. 3, 2022, 4:45 p.m.