Package: netSmooth 1.33.0

Jonathan Ronen

netSmooth: Network smoothing for scRNAseq

netSmooth is an R package for network smoothing of single cell RNA sequencing data. Using bio networks such as protein-protein interactions as priors for gene co-expression, netsmooth improves cell type identification from noisy, sparse scRNAseq data.

Authors:Jonathan Ronen [aut, cre], Altuna Akalin [aut]

netSmooth_1.33.0.tar.gz
netSmooth_1.33.0.zip(r-4.7)netSmooth_1.33.0.zip(r-4.6)netSmooth_1.33.0.zip(r-4.5)
netSmooth_1.33.0.tgz(r-4.6-any)netSmooth_1.33.0.tgz(r-4.5-any)
netSmooth_1.33.0.tar.gz(r-4.7-any)netSmooth_1.33.0.tar.gz(r-4.6-any)
netSmooth_1.33.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
netSmooth/json (API)

# Install 'netSmooth' in R:

install.packages('netSmooth', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bimsbbioinfo/netsmooth/issues

Datasets:

human.ppi - Human Protein-Protein interaction graph
mouse.ppi - Mouse Protein-Protein interaction graph
smallPPI - A small human Protein-Protein interaction graph for use in examples.
smallscRNAseq - A small single cell RNA-seq dataset for use in examples.

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

network graphandnetwork singlecell rnaseq geneexpression sequencing transcriptomics normalization preprocessing clustering dimensionreduction bioinformatics genomics single-cell

7.44 score 29 stars 4 scripts 398 downloads 8 mentions 3 exports 165 dependencies

Last updated from:8810a5039a. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	252
linux-devel-x86_64	NOTE	635
source / vignettes	OK	416
linux-release-x86_64	NOTE	525
macos-release-arm64	NOTE	302
macos-oldrel-arm64	NOTE	328
windows-devel	NOTE	621
windows-release	NOTE	655
windows-oldrel	NOTE	411
wasm-release	OK	218

Exports:netSmooth pickDimReduction robustClusters

Dependencies:abind ade4 annotate AnnotationDbi ape askpass assorthead base64enc beachmat beeswarm benchmarkme benchmarkmeData BH Biobase BiocGenerics biocmake BiocManager BiocNeighbors BiocParallel BiocSingular Biostrings bit bit64 blob cachem Cairo cli cluster clusterExperiment ClusterR codetools colorspace cpp11 crayon curl data.table DBI DelayedArray digest dir.expiry doParallel dplyr dqrng edgeR entropy farver fastmap filelock FNN foreach formatR futile.logger futile.options genefilter generics GenomicRanges ggbeeswarm ggplot2 ggrastr ggrepel glue gmp gridBase gridExtra gtable h5mread HDF5Array hms httr IRanges irlba isoband iterators jsonlite KEGGREST kernlab labeling lambda.r lattice lifecycle limma locfdr locfit magrittr MASS Matrix MatrixGenerics matrixStats mbkmeans memoise mime nlme NMF openssl pheatmap phylobase pillar pixmap pkgconfig plyr png pracma prettyunits progress purrr R6 ragg RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppEigen RcppML RcppProgress registry reshape2 rhdf5 rhdf5filters Rhdf5lib rlang rncl RNeXML rngtools RSpectra RSQLite rsvd Rtsne S4Arrays S4Vectors S7 ScaledMatrix scales scater scuttle Seqinfo SingleCellExperiment sitmo snow softImpute sp SparseArray statmod stringi stringr SummarizedExperiment survival sys systemfonts textshaping tibble tidyr tidyselect utf8 uuid uwot vctrs vipor viridis viridisLite withr XML xml2 xtable XVector zinbwave

Building PPIs from StringDB

Jonathan Ronen, Altuna Akalin

Rendered frombuildingPPIsFromStringDB.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2019-10-23
Started: 2018-01-31

Introduction to netSmooth package

Jonathan Ronen, Altuna Akalin

Rendered fromnetSmoothIntro.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2019-12-16
Started: 2017-12-11

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Human Protein-Protein interaction graph	human.ppi
Mouse Protein-Protein interaction graph	mouse.ppi
Perform network smoothing of gene expression or other omics data	netSmooth netSmooth,DelayedMatrix-method netSmooth,Matrix-method netSmooth,matrix-method netSmooth,SingleCellExperiment-method netSmooth,SummarizedExperiment-method
Pick the dimensionality reduction method for a dataset that gives the 2D embedding with the highest entropy	pickDimReduction pickDimReduction,DelayedMatrix-method pickDimReduction,Matrix-method pickDimReduction,matrix-method pickDimReduction,SummarizedExperiment-method
Perform robust clustering on dataset, and calculate the proportion of samples in robust clusters	robustClusters robustClusters,matrix-method robustClusters,SummarizedExperiment-method
A small human Protein-Protein interaction graph for use in examples.	smallPPI
A small single cell RNA-seq dataset for use in examples.	smallscRNAseq