RCSL

This package is for version 3.19 of Bioconductor; for the stable, up-to-date release version, see RCSL.

Rank Constrained Similarity Learning for single cell RNA sequencing data


Bioconductor version: 3.19

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 "4.4") 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")
RCSL package manual HTML R Script
Reference Manual PDF

Details

biocViews Clustering, DimensionReduction, RNASeq, Sequencing, SingleCell, Software, Visualization
Version 1.12.0
In Bioconductor since BioC 3.13 (R-4.1) (3.5 years)
License Artistic-2.0
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
System Requirements
URL https://github.com/QinglinMei/RCSL
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Suggests testthat, knitr, BiocStyle, rmarkdown, mclust, tidyverse, tinytex
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Package Archives

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

Source Package RCSL_1.12.0.tar.gz
Windows Binary (x86_64) RCSL_1.12.0.zip
macOS Binary (x86_64) RCSL_1.12.0.tgz
macOS Binary (arm64) RCSL_1.12.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/RCSL
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/RCSL
Bioc Package Browser https://code.bioconductor.org/browse/RCSL/
Package Short Url https://bioconductor.org/packages/RCSL/
Package Downloads Report Download Stats