Package: diffuStats
Type: Package
Title: Diffusion scores on biological networks
Version: 1.4.0
Author: Sergio Picart-Armada and Alexandre Perera-Lluna
Maintainer: Sergio Picart-Armada <sergi.picart@upc.edu>
Description: Label propagation approaches are a widely used 
    procedure in computational biology for giving context
    to molecular entities using network data.
    Node labels, which can derive from gene expression,
    genome-wide association studies,
    protein domains or metabolomics profiling,
    are propagated to their neighbours in the network,
    effectively smoothing the scores through
    prior annotated knowledge and prioritising novel candidates.
    The R package diffuStats contains a 
    collection of diffusion kernels and scoring approaches
    that facilitates their computation and benchmarking.
Depends: R (>= 3.4)
Imports: grDevices, stats, methods, Matrix, MASS, expm, igraph, Rcpp,
        RcppArmadillo, RcppParallel, plyr, precrec
License: GPL-3
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.0.1
Suggests: testthat, knitr, rmarkdown, ggplot2, ggsci, igraphdata,
        BiocStyle, reshape2
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
SystemRequirements: GNU make
VignetteBuilder: knitr
biocViews: Network, GeneExpression, GraphAndNetwork
git_url: https://git.bioconductor.org/packages/diffuStats
git_branch: RELEASE_3_9
git_last_commit: aeb2e21
git_last_commit_date: 2019-05-02
Date/Publication: 2019-05-02
NeedsCompilation: yes
Packaged: 2019-05-03 04:07:01 UTC; biocbuild
Built: R 3.6.0; x86_64-apple-darwin15.6.0; 2019-05-03 14:26:22 UTC; unix
