DOI: 10.18129/B9.bioc.deco  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see deco.

Decomposing Heterogeneous Cohorts using Omic Data Profiling

Bioconductor version: 3.17

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>

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biocViews Bayesian, BiomedicalInformatics, Clustering, DifferentialExpression, ExonArray, FeatureExtraction, GeneExpression, MicroRNAArray, Microarray, MultipleComparison, Proteomics, RNASeq, Sequencing, Software, Transcription, Transcriptomics, mRNAMicroarray
Version 1.16.0
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
Suggests knitr, curatedTCGAData, MultiAssayExperiment, Homo.sapiens, rmarkdown
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