recipe bioconductor-indeed

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






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.

package bioconductor-indeed

(downloads) docker_bioconductor-indeed


2.2.0-0, 2.0.0-0, 1.2.0-1, 1.2.0-0, 1.0.1-0

Required By


With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-indeed

and update with:

conda update bioconductor-indeed

or use the docker container:

docker pull<tag>

(see bioconductor-indeed/tags for valid values for <tag>)