RCSL
This is the development version of RCSL; for the stable release version, see RCSL.
All Bioconductor versions of RCSL
3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13
Rank Constrained Similarity Learning for single cell RNA sequencing data
Bioconductor version: 3.24 · Package version: 1.21.0
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.
Author: Qinglin Mei [cre, aut], Guojun Li [fnd], Zhengchang Su [fnd]
Maintainer: Qinglin Mei <meiqinglinkf at 163.com>
Citation
From within R, enter citation("RCSL"):
Qinglin Mei. RCSL: Rank Constrained Similarity Learning for single cell RNA sequencing data. doi:10.18129/B9.bioc.RCSL, R package version 1.21.0, https://bioconductor.org/packages/RCSL.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")
BiocManager::install("RCSL")For older versions of R, please refer to the appropriate Bioconductor release.
Details
| Version | 1.21.0 |
| License | Artistic-2.0 |
| URL | https://github.com/QinglinMei/RCSL |
| Last updated | 2026-04-28 |
| In Bioconductor since | BioC 3.13 (R-4.1) (5 years) |
| Downloads rank | 1729 of 2,456 |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | Clustering, DimensionReduction, RNASeq, Sequencing, SingleCell, Software, Visualization |
| Package Short Url | https://bioconductor.org/packages/RCSL/ |
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RCSL")| A quick tour of RCSL | HTML | R Script |
| Reference Manual |
Download
Follow the installation instructions to use this package in your R session.
| Source package | RCSL_1.21.0.tar.gz |
| Windows binary (x86_64) | RCSL_1.21.0.zip |
| macOS binary (arm64) | RCSL_1.21.0.tgz |
| macOS binary (x86_64) | RCSL_1.21.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/RCSL |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/RCSL |
| Package Downloads Report | Download Stats |
Dependencies
Depends: R (>= 4.1)
Imports: RcppAnnoy, igraph, NbClust, Rtsne, ggplot2 (>= 3.4.0), methods, pracma, umap, grDevices, graphics, stats, Rcpp (>= 0.11.0), MatrixGenerics, SingleCellExperiment
Suggests: testthat, knitr, BiocStyle, rmarkdown, mclust, tidyverse, tinytex