Package: diffuStats 1.33.0

Sergio Picart-Armada

diffuStats: Diffusion scores on biological networks

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.

Authors:Sergio Picart-Armada [aut, cre], Alexandre Perera-Lluna [aut]

diffuStats_1.33.0.tar.gz
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diffuStats_1.33.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
diffuStats/json (API)
NEWS

# Install 'diffuStats' in R:
install.packages('diffuStats', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On BioConductor:diffuStats-1.33.0(bioc 3.24)diffuStats-1.32.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

networkgeneexpressiongraphandnetworkmetabolomicstranscriptomicsproteomicsgeneticsgenomewideassociationnormalizationcpp

5.43 score 45 scripts 414 downloads 3 mentions 24 exports 34 dependencies

Last updated from:58da991e25. Checks:1 WARNING, 8 NOTE, 2 OK, 3 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING176
linux-devel-arm64NOTE183
linux-devel-x86_64NOTE191
source / vignettesOK281
linux-release-arm64NOTE180
linux-release-x86_64NOTE228
macos-release-arm64NOTE145
macos-release-x86_64NOTE268
macos-oldrel-arm64FAIL82
macos-oldrel-x86_64FAIL161
windows-develNOTE165
windows-releaseNOTE159
windows-oldrelFAIL81
wasm-releaseOK139

Exports:commuteTimeKerneldiffusediffuse_griddiffuse_mcdiffuse_rawdiffusionKernelgenerate_graphgenerate_inputget_covarget_muget_mu_referenceget_var_referenceinverseCosineKernelis_kernellargest_ccmetric_aucmetric_funperfperf_evalperf_wilcoxpStepKernelregularisedLaplacianKernelscores2coloursscores2shapes

Dependencies:assertthatbackportscheckmateclicpp11data.tableexpmfarverggplot2gluegridExtragtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixpkgconfigplyrprecrecR6RColorBrewerRcppRcppArmadilloRcppParallelrlangS7scalesvctrsviridisLitewithr

Case study: predicting protein function

Rendered fromdiffuStats.Rnwusingutils::Sweaveon May 23 2026.

Last update: 2019-03-28
Started: 2017-06-27

Diffusion using diffuStats in a nutshell

Rendered fromintro.Rmdusingknitr::rmarkdownon May 23 2026.

Last update: 2017-07-13
Started: 2017-02-28

Readme and manuals

Help Manual

Help pageTopics
Sanity checks for input.available_methods .check_graph .check_K .check_method .check_metric .check_scores
Function to connect a non connected graph.connect_undirected_graph
Generate data.frame with default vertex attributes.default_graph_param .default_prop
S4 sparse matrix to arma::sp_matconvertSparse
Diffuse scores on a networkdiffuse diffuse_grid
Compute the heatrank using permutationsdiffuse_mc
Diffuse scores on a networkdiffuse_raw
diffuStats: an R package to compute and benchmark diffusion scoresdiffuStats
Generate a random graphgenerate_graph
Generate a random input for graph diffusiongenerate_input
Toy graph to play with diffusiongraph_toy
Check if a matrix is a valid kernelis_kernel
Compute graph kernelscommuteTimeKernel diffusionKernel inverseCosineKernel kernels pStepKernel regularisedLaplacianKernel
Largest connected componentlargest_cc
Compute the area under the curves (ROC, PRC)metric_auc metric_fun
Compute exact statistical momentsget_covar get_mu get_mu_reference get_var_reference moments
Create a named listnamed.list
Compute heatrank in parallelParallelHeatrank
Compare diffusions to a target score on a grid of parametersperf
Compute performance of diffusion scores on a single caseperf_eval
Compute column-wise statistics in a performance matrixperf_wilcox
Translate values into coloursscores2colours
Translate values into shapesscores2shapes
Compute heatrank for a single caseserialHeatrank
Sparsify arma::mat into arma::sp_matsparsify2
Convert input to list formatto_list
Convert list format to desired formatto_x_from_list
In which format is the input?which_format