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deco

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

This is the development version of deco; for the stable release version, see deco.

Decomposing Heterogeneous Cohorts using Omic Data Profiling

Bioconductor version: Development (3.18)

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 "4.3") and enter: 

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("deco")

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

Documentation

Reference Manual PDF

Details

biocViews Bayesian, BiomedicalInformatics, Clustering, DifferentialExpression, ExonArray, FeatureExtraction, GeneExpression, MicroRNAArray, Microarray, MultipleComparison, Proteomics, RNASeq, Sequencing, Software, Transcription, Transcriptomics, mRNAMicroarray
Version 1.17.1
In Bioconductor since BioC 3.9 (R-3.6) (4.5 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
Linking To
Suggests knitr, curatedTCGAData, MultiAssayExperiment, Homo.sapiens, rmarkdown
System Requirements
Enhances
URL https://github.com/fjcamlab/deco
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Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/deco
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/deco
Package Short Url https://bioconductor.org/packages/deco/
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