Package: diffuStats
Type: Package
Title: Diffusion scores on biological networks
Version: 1.26.0
Authors@R: c(
    person(
        "Sergio", "Picart-Armada", role = c("aut", "cre"),
        email = "sergi.picart@upc.edu"), 
    person(
        "Alexandre", "Perera-Lluna", role = c("aut"),
        email = "alexandre.perera@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, characterisation and benchmarking.
Depends: R (>= 3.4)
Imports: grDevices, stats, methods, Matrix, MASS, checkmate, expm,
        igraph, Rcpp, RcppArmadillo, RcppParallel, plyr, precrec
License: GPL-3
LazyData: true
Encoding: UTF-8
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown, ggplot2, ggsci, igraphdata,
        BiocStyle, reshape2, utils
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
SystemRequirements: GNU make
VignetteBuilder: knitr
biocViews: Network, GeneExpression, GraphAndNetwork, Metabolomics,
        Transcriptomics, Proteomics, Genetics, GenomeWideAssociation,
        Normalization
git_url: https://git.bioconductor.org/packages/diffuStats
git_branch: RELEASE_3_20
git_last_commit: f1d4aaa
git_last_commit_date: 2024-10-29
Repository: Bioconductor 3.20
Date/Publication: 2024-10-29
NeedsCompilation: yes
Packaged: 2024-10-30 02:16:30 UTC; biocbuild
Author: Sergio Picart-Armada [aut, cre],
  Alexandre Perera-Lluna [aut]
Maintainer: Sergio Picart-Armada <sergi.picart@upc.edu>
Built: R 4.4.1; x86_64-w64-mingw32; 2024-10-30 15:47:35 UTC; windows
Archs: x64
