DOI: 10.18129/B9.bioc.diffuStats    

Diffusion scores on biological networks

Bioconductor version: Release (3.6)

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.

Author: Sergio Picart-Armada and Alexandre Perera-Lluna

Maintainer: Sergio Picart-Armada <sergi.picart at upc.edu>

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biocViews GeneExpression, GraphAndNetwork, Network, Software
Version 0.102.0
License GPL-3
Depends R (>= 3.4)
Imports grDevices, stats, methods, Matrix, MASS, expm, igraph, Rcpp, RcppArmadillo, RcppParallel, plyr, precrec
LinkingTo Rcpp, RcppArmadillo, RcppParallel
Suggests testthat, knitr, rmarkdown, ggplot2, ggsci, igraphdata, BiocStyle, reshape2
SystemRequirements GNU make
Depends On Me
Imports Me
Suggests Me
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Source Package diffuStats_0.102.0.tar.gz
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Source Repository git clone https://git.bioconductor.org/packages/diffuStats
Package Short Url http://bioconductor.org/packages/diffuStats/
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