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 <[email protected]>
LicenseGPL (>=3)
Version1.2.0
URL https://github.com/fjcamlab/deco
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("deco")

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deco documentation built on Oct. 31, 2019, 8:36 a.m.