Package: diffuStats
Type: Package
Title: Diffusion scores on biological networks
Version: 1.31.0
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: devel
git_last_commit: 5cda747
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
