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RCSL

This is thereleased version of RCSL; for the devel version, seeRCSL.

Rank Constrained Similarity Learning for single cell RNA sequencing data

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DOI: 10.18129/B9.bioc.RCSL


Bioconductor version: Release (3.22)

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, entercitation("RCSL")):

Installation

To install this package, start R (version "4.5") and enter:

if (!require("BiocManager", quietly = TRUE))    install.packages("BiocManager")BiocManager::install("RCSL")

For older versions of R, please refer to the appropriateBioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("RCSL")
RCSL package manualHTMLR Script
Reference ManualPDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViewsClustering,DimensionReduction,RNASeq,Sequencing,SingleCell,Software,Visualization
Version1.18.0
In Bioconductor sinceBioC 3.13 (R-4.1) (4.5 years)
LicenseArtistic-2.0
DependsR (>= 4.1)
ImportsRcppAnnoy,igraph,NbClust,Rtsne,ggplot2 (>= 3.4.0), methods,pracma,umap, grDevices, graphics, stats,Rcpp (>= 0.11.0),MatrixGenerics,SingleCellExperiment
System Requirements
URLhttps://github.com/QinglinMei/RCSL
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Package Archives

FollowInstallation instructions to use this package in your R session.

Source PackageRCSL_1.18.0.tar.gz
Windows Binary (x86_64) RCSL_1.18.0.zip (64-bit only)
macOS Binary (x86_64)RCSL_1.18.0.tgz
macOS Binary (arm64)RCSL_1.18.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/RCSL
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/RCSL
Bioc Package Browserhttps://code.bioconductor.org/browse/RCSL/
Package Short Urlhttps://bioconductor.org/packages/RCSL/
Package Downloads ReportDownload Stats

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