deco: Decomposing Heterogeneous Cohorts using Omic Data Profiling

This package discovers differential features in hetero- and homogeneous omic data by a two-step method including subsampling LIMMA and NSCA. DECO reveals feature associations to hidden subclasses not exclusively related to higher deregulation levels.

Package details

AuthorFrancisco Jose Campos-Laborie, Jose Manuel Sanchez-Santos and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain.
Bioconductor views Bayesian BiomedicalInformatics Clustering DifferentialExpression ExonArray FeatureExtraction GeneExpression MicroRNAArray Microarray MultipleComparison Proteomics RNASeq Sequencing Software Transcription Transcriptomics mRNAMicroarray
MaintainerFrancisco Jose Campos Laborie <>
LicenseGPL (>=3)
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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deco documentation built on Nov. 8, 2020, 7:45 p.m.