Package: netSmooth 1.27.0
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:
netSmooth_1.27.0.tar.gz
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netSmooth.pdf |netSmooth.html✨
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
- 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-1.25.0(bioc 3.20)netSmooth-1.24.0(bioc 3.19)
networkgraphandnetworksinglecellrnaseqgeneexpressionsequencingtranscriptomicsnormalizationpreprocessingclusteringdimensionreductionbioinformaticsgenomicssingle-cell
Last updated 23 days agofrom:4d3aa762ad. Checks:OK: 1 NOTE: 5 ERROR: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | NOTE | Oct 31 2024 |
R-4.5-linux | NOTE | Oct 30 2024 |
R-4.4-win | NOTE | Oct 31 2024 |
R-4.4-mac | NOTE | Oct 31 2024 |
R-4.3-win | NOTE | Oct 31 2024 |
R-4.3-mac | ERROR | Oct 31 2024 |
Exports:netSmoothpickDimReductionrobustClusters
Dependencies:abindade4annotateAnnotationDbiapeaskpassassortheadbeachmatbeeswarmbenchmarkmebenchmarkmeDataBHBiobaseBiocGenericsBiocManagerBiocNeighborsBiocParallelBiocSingularBiostringsbitbit64blobcachemCairocliclusterclusterExperimentClusterRcodetoolscolorspacecpp11crayoncurldata.tableDBIDelayedArraydigestdoParalleldplyrdqrngedgeRentropyfansifarverfastmapFNNforeachformatRfutile.loggerfutile.optionsgenefiltergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggbeeswarmggplot2ggrastrggrepelgluegmpgridBasegridExtragtableHDF5ArrayhmshttrIRangesirlbaisobanditeratorsjsonliteKEGGRESTkernlablabelinglambda.rlatticelifecyclelimmalocfdrlocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmbkmeansmemoisemgcvmimemunsellnlmeNMFopensslpheatmapphylobasepillarpixmappkgconfigplogrplyrpngpracmaprettyunitsprogresspurrrR6raggRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppMLRcppProgressregistryreshape2rhdf5rhdf5filtersRhdf5librlangrnclRNeXMLrngtoolsRSpectraRSQLitersvdRtsneS4ArraysS4VectorsScaledMatrixscalesscaterscuttleSingleCellExperimentsitmosnowsoftImputespSparseArraystatmodstringistringrSummarizedExperimentsurvivalsyssystemfontstextshapingtibbletidyrtidyselectUCSC.utilsutf8uuiduwotvctrsviporviridisviridisLitewithrXMLxml2xtableXVectorzinbwavezlibbioc
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 |