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-any)netSmooth_1.33.0.zip(r-4.6-any)netSmooth_1.33.0.zip(r-4.5-any)
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✨
DESCRIPTION
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)

networkgraphandnetworksinglecellrnaseqgeneexpressionsequencingtranscriptomicsnormalizationpreprocessingclusteringdimensionreductionbioinformaticsgenomicssingle-cell

7.46 score 30 stars 9 scripts 554 downloads 8 mentions 3 exports 160 dependencies

Last updated from:8810a5039a. Checks:1 WARNING, 5 NOTE, 2 OK, 2 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING279
linux-develNOTE630
source / vignettesOK342
linux-releaseNOTE576
macos-releaseNOTE366
macos-oldrelFAIL111
windows-develNOTE479
windows-releaseNOTE455
windows-oldrelFAIL423
wasm-releaseOK181

Exports:netSmoothpickDimReductionrobustClusters

Dependencies:abindade4annotateAnnotationDbiapeaskpassassortheadbeachmatbeeswarmbenchmarkmebenchmarkmeDataBHBiobaseBiocBaseUtilsBiocGenericsbiocmakeBiocManagerBiocNeighborsBiocParallelBiocSingularBiostringsbitbit64blobcachemcliclusterclusterExperimentClusterRcodetoolscolorspacecpp11crayoncurldata.tableDBIDelayedArraydigestdir.expirydoParalleldplyrdqrngedgeRentropyfarverfastmapfilelockFNNforeachformatRfutile.loggerfutile.optionsgenefiltergenericsGenomicRangesggbeeswarmggplot2ggrepelgluegmpgridBasegridExtragtableh5mreadHDF5ArrayhmshttrIRangesirlbaisobanditeratorsjsonliteKEGGRESTkernlablabelinglambda.rlatticelifecyclelimmalocfdrlocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmbkmeansmemoisemimenlmeNMFopensslpheatmapphylobasepillarpixmappkgconfigplyrpngpracmaprettyunitsprogresspurrrR6RColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppMLRcppProgressregistryreshape2rhdf5rhdf5filtersRhdf5librlangrnclRNeXMLrngtoolsRSpectraRSQLitersvdRtsneS4ArraysS4VectorsS7ScaledMatrixscalesscaterscuttleSeqinfoSingleCellExperimentsitmosnowsoftImputespSparseArraystatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselectutf8uuiduwotvctrsviporviridisviridisLitewithrXMLxml2xtableXVectorzinbwave

Introduction to netSmooth package
Introduction | Smoothing single-cell gene expression data with netSmooth() function | Optimizing the smoothing parameter alpha | Getting robust clusters from data | Deciding for the best dimension reduction method for visualization and clustering | Frequently asked questions | How can I make smoothing faster ? | What happens if all the genes are not in my network ?
Rendered fromnetSmoothIntro.Rmdusingknitr::rmarkdown

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

Building PPIs from StringDB
Introduction | Obtaining network data from stringDB
Rendered frombuildingPPIsFromStringDB.Rmdusingknitr::rmarkdown

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

Readme and manuals

Help Manual

Help pageTopics
Human Protein-Protein interaction graphhuman.ppi
Mouse Protein-Protein interaction graphmouse.ppi
Perform network smoothing of gene expression or other omics datanetSmooth 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 entropypickDimReduction 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 clustersrobustClusters 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