Package: Pigengene
Type: Package
Title: Infers biological signatures from gene expression data
Version: 1.10.0
Date: 2016-03-31
Author: Habil Zare, Amir Foroushani, and Rupesh Agrahari
Maintainer: Habil Zare <zare@u.washington.edu>
biocViews: GeneExpression, RNASeq, NetworkInference, Network,
        GraphAndNetwork, BiomedicalInformatics, SystemsBiology,
        Transcriptomics, Classification, Clustering, DecisionTree,
        DimensionReduction, PrincipalComponent, Microarray,
        Normalization, ImmunoOncology
Depends: R (>= 3.3.0), graph
Description: Pigengene package provides an efficient way to infer
        biological signatures from gene expression profiles. The
        signatures are independent from the underlying platform, e.g.,
        the input can be microarray or RNA Seq data. It can even infer
        the signatures using data from one platform, and evaluate them
        on the other. Pigengene identifies the modules (clusters) of
        highly coexpressed genes using coexpression network analysis,
        summarizes the biological information of each module in an
        eigengene, learns a Bayesian network that models the
        probabilistic dependencies between modules, and builds a
        decision tree based on the expression of eigengenes.
License: GPL (>=2)
Imports: bnlearn (>= 4.4.1), C50 (>= 0.1.2), MASS, matrixStats,
        partykit, Rgraphviz, WGCNA, GO.db, impute, preprocessCore,
        grDevices, graphics, stats, utils, parallel, pheatmap (>=
        1.0.8)
Suggests: org.Hs.eg.db (>= 3.7.0), org.Mm.eg.db (>= 3.7.0), biomaRt (>=
        2.30.0), knitr, BiocStyle, AnnotationDbi, energy
VignetteBuilder: knitr
NeedsCompilation: no
git_url: https://git.bioconductor.org/packages/Pigengene
git_branch: RELEASE_3_9
git_last_commit: fb16e07
git_last_commit_date: 2019-05-02
Date/Publication: 2019-05-02
Packaged: 2019-05-03 04:12:49 UTC; biocbuild
Built: R 3.6.0; ; 2019-05-03 14:07:51 UTC; windows
