This is the development version of diffuStats; for the stable release version, see diffuStats.
Diffusion scores on biological networksBioconductor version: Development (3.22)
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.
Author: Sergio Picart-Armada [aut, cre], Alexandre Perera-Lluna [aut]
Maintainer: Sergio Picart-Armada <sergi.picart at upc.edu>
Citation (from within R, entercitation("diffuStats")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("diffuStats")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("diffuStats")Follow Installation instructions to use this package in your R session.
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