Package: scmap 1.29.0
scmap: A tool for unsupervised projection of single cell RNA-seq data
Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment on to the cell-types or individual cells identified in a different experiment.
Authors:
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scmap.pdf |scmap.html✨
scmap/json (API)
NEWS
# Install 'scmap' in R: |
install.packages('scmap', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/hemberg-lab/scmap/issues
On BioConductor:scmap-1.29.0(bioc 3.21)scmap-1.28.0(bioc 3.20)
immunooncologysinglecellsoftwareclassificationsupportvectormachinernaseqvisualizationtranscriptomicsdatarepresentationtranscriptionsequencingpreprocessinggeneexpressiondataimportbioconductor-packagehuman-cell-atlasprojection-mappingsingle-cell-rna-seqopenblascpp
Last updated 2 months agofrom:4a84aef909. Checks:OK: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 04 2024 |
R-4.5-win-x86_64 | NOTE | Dec 04 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 04 2024 |
R-4.4-win-x86_64 | NOTE | Dec 04 2024 |
R-4.4-mac-x86_64 | NOTE | Dec 04 2024 |
R-4.4-mac-aarch64 | NOTE | Dec 04 2024 |
R-4.3-win-x86_64 | NOTE | Dec 04 2024 |
R-4.3-mac-x86_64 | NOTE | Dec 04 2024 |
R-4.3-mac-aarch64 | NOTE | Dec 04 2024 |
Exports:getSankeyindexCellindexClusterscmapCellscmapCell2ClusterscmapClusterselectFeaturessetFeatures
Dependencies:abindaskpassBiobaseBiocGenericsclassclicolorspacecrayoncurlDelayedArraydplyre1071fansifarvergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegoogleVisgtablehttrIRangesisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpillarpkgconfigplyrproxyR6randomForestRColorBrewerRcppRcppArmadilloreshape2rlangS4ArraysS4VectorsscalesSingleCellExperimentSparseArraystringistringrSummarizedExperimentsystibbletidyselectUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc