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>

Installation

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

if (!require("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) (1 year)
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