Package: RCSL 1.21.0

Qinglin Mei

RCSL: Rank Constrained Similarity Learning for single cell RNA sequencing data

A novel clustering algorithm and toolkit RCSL (Rank Constrained Similarity Learning) to accurately identify various cell types using scRNA-seq data from a complex tissue. RCSL considers both lo-cal similarity and global similarity among the cells to discern the subtle differences among cells of the same type as well as larger differences among cells of different types. RCSL uses Spearman’s rank correlations of a cell’s expression vector with those of other cells to measure its global similar-ity, and adaptively learns neighbour representation of a cell as its local similarity. The overall similar-ity of a cell to other cells is a linear combination of its global similarity and local similarity.

Authors:Qinglin Mei [cre, aut], Guojun Li [fnd], Zhengchang Su [fnd]

RCSL_1.21.0.tar.gz
RCSL_1.21.0.zip(r-4.7)RCSL_1.21.0.zip(r-4.6)RCSL_1.21.0.zip(r-4.5)
RCSL_1.21.0.tgz(r-4.6-any)RCSL_1.21.0.tgz(r-4.5-any)
RCSL_1.21.0.tar.gz(r-4.7-any)RCSL_1.21.0.tar.gz(r-4.6-any)
RCSL_1.21.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
RCSL/json (API)

# Install 'RCSL' in R:
install.packages('RCSL', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/qinglinmei/rcsl/issues

Datasets:
  • ann - Cell type annotations of 'yan' datasets by Yan et al.
  • yan - A public scRNA-seq dataset by Yan et al.

On BioConductor:RCSL-1.21.0(bioc 3.24)RCSL-1.20.0(bioc 3.23)

singlecellsoftwareclusteringdimensionreductionrnaseqvisualizationsequencing

4.51 score 2 stars 16 scripts 331 downloads 11 exports 56 dependencies

Last updated from:daa9941f16. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING167
linux-devel-x86_64NOTE427
source / vignettesOK234
linux-release-x86_64NOTE447
macos-release-arm64NOTE267
macos-oldrel-arm64NOTE232
windows-develNOTE758
windows-releaseNOTE267
windows-oldrelNOTE981
wasm-releaseOK137

Exports:BDSMEstClustersGenesFiltergetLineageNeigRepresentPlotMSTPlotPseudoTimePlotTrajectoryRCSLSimSTrajectoryAnalysis

Dependencies:abindaskpassBiobaseBiocGenericsclicpp11DelayedArrayfarvergenericsGenomicRangesggplot2gluegtablehereigraphIRangesisobandjsonlitelabelinglatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsNbClustopensslpkgconfigpngpracmaR6rappdirsRColorBrewerRcppRcppAnnoyRcppEigenRcppTOMLreticulaterlangrprojrootRSpectraRtsneS4ArraysS4VectorsS7scalesSeqinfoSingleCellExperimentSparseArraySummarizedExperimentsysumapvctrsviridisLitewithrXVector

A quick tour of RCSL

Rendered fromRCSL.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2024-02-15
Started: 2021-04-03