deco

DOI: 10.18129/B9.bioc.deco  

Decomposing Heterogeneous Cohorts using Omic Data Profiling

Bioconductor version: Release (3.16)

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.

Author: Francisco 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.

Maintainer: Francisco Jose Campos Laborie <fjcamlab at gmail.com>

Citation (from within R, enter citation("deco")):

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("deco")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("deco")

 

HTML R Script deco
PDF   Reference Manual
Text   NEWS

Details

biocViews Bayesian, BiomedicalInformatics, Clustering, DifferentialExpression, ExonArray, FeatureExtraction, GeneExpression, MicroRNAArray, Microarray, MultipleComparison, Proteomics, RNASeq, Sequencing, Software, Transcription, Transcriptomics, mRNAMicroarray
Version 1.13.0
In Bioconductor since BioC 3.9 (R-3.6) (4 years)
License GPL (>=3)
Depends R (>= 3.5.0), AnnotationDbi, BiocParallel, SummarizedExperiment, limma
Imports stats, methods, ggplot2, foreign, graphics, BiocStyle, Biobase, cluster, gplots, RColorBrewer, locfit, made4, ade4, sfsmisc, scatterplot3d, gdata, grDevices, utils, reshape2, gridExtra
LinkingTo
Suggests knitr, curatedTCGAData, MultiAssayExperiment, Homo.sapiens, rmarkdown
SystemRequirements
Enhances
URL https://github.com/fjcamlab/deco
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package deco_1.13.0.tar.gz
Windows Binary deco_1.14.0.zip
macOS Binary (x86_64) deco_1.14.0.tgz
macOS Binary (arm64) deco_1.14.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/deco
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/deco
Bioc Package Browser https://code.bioconductor.org/browse/deco/
Package Short Url https://bioconductor.org/packages/deco/
Package Downloads Report Download Stats

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