Package: deco
Type: Package
Title: Decomposing Heterogeneous Cohorts using Omic Data Profiling
Version: 1.2.0
Date: 2019-03-27
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@gmail.com>
biocViews: Software, FeatureExtraction, Clustering, MultipleComparison,
        DifferentialExpression, Transcriptomics, BiomedicalInformatics,
        Proteomics, Bayesian, GeneExpression, Transcription,
        Sequencing, Microarray, ExonArray, RNASeq, MicroRNAArray,
        mRNAMicroarray
Description: 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.
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
License: GPL (>=3)
URL: https://github.com/fjcamlab/deco
ZipData: true
LazyLoad: true
VignetteBuilder: knitr
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2019-10-30 04:48:23 UTC; biocbuild
git_url: https://git.bioconductor.org/packages/deco
git_branch: RELEASE_3_10
git_last_commit: 5587eaf
git_last_commit_date: 2019-10-29
Date/Publication: 2019-10-29
Built: R 3.6.1; ; 2019-10-30 13:02:58 UTC; windows
