Bioc2026 Registration Open!

diffuStats

Diffusion scores on biological networks

Bioconductor version: 3.23 · Package version: 1.32.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("diffuStats")

Details

MaintainerSergio Picart-Armada <sergi.picart@upc.edu>
AuthorSergio Picart-Armada [aut, cre], Alexandre Perera-Lluna [aut]
LicenseGPL-3
System RequirementsGNU make
Downloads rank291
Source branchRELEASE_3_23
biocViewsGeneExpression, Genetics, GenomeWideAssociation, GraphAndNetwork, Metabolomics, Network, Normalization, Proteomics, Software, Transcriptomics

Documentation

Download

Dependencies

Depends: R (>= 3.4)

Imports: grDevices, stats, methods, Matrix, MASS, checkmate, expm, igraph, Rcpp, RcppArmadillo, RcppParallel, plyr, precrec

LinkingTo: Rcpp, RcppArmadillo, RcppParallel

Suggests: testthat, knitr, rmarkdown, ggplot2, ggsci, igraphdata, BiocStyle, reshape2, utils