RCSL

DOI: 10.18129/B9.bioc.RCSL    

Rank Constrained Similarity Learning for single cell RNA sequencing data

Bioconductor version: Release (3.14)

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")):

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("RCSL")

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

Documentation

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

browseVignettes("RCSL")

 

HTML R Script RCSL package manual
PDF   Reference Manual

Details

biocViews Clustering, DimensionReduction, RNASeq, Sequencing, SingleCell, Software, Visualization
Version 1.2.0
In Bioconductor since BioC 3.13 (R-4.1) (0.5 years)
License GPL-3
Depends R (>= 4.1)
Imports RcppAnnoy, igraph, NbClust, Rtsne, ggplot2, methods, pracma, umap, grDevices, graphics, stats
LinkingTo
Suggests knitr, rmarkdown, mclust, RcppAnnoy
SystemRequirements
Enhances
URL https://github.com/QinglinMei/RCSL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package RCSL_1.2.0.tar.gz
Windows Binary RCSL_1.2.0.zip
macOS 10.13 (High Sierra) RCSL_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/RCSL
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/RCSL
Package Short Url https://bioconductor.org/packages/RCSL/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.14 Source Archive

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