SIMLR

This is the development version of SIMLR; for the stable release version, see SIMLR.

Single-cell Interpretation via Multi-kernel LeaRning (SIMLR)

Bioconductor version: Development (3.21)

Single-cell RNA-seq technologies enable high throughput gene expression measurement of individual cells, and allow the discovery of heterogeneity within cell populations. Measurement of cell-to-cell gene expression similarity is critical for the identification, visualization and analysis of cell populations. However, single-cell data introduce challenges to conventional measures of gene expression similarity because of the high level of noise, outliers and dropouts. We develop a novel similarity-learning framework, SIMLR (Single-cell Interpretation via Multi-kernel LeaRning), which learns an appropriate distance metric from the data for dimension reduction, clustering and visualization.

Author: Daniele Ramazzotti [aut] (ORCID: ), Bo Wang [aut], Luca De Sano [cre, aut] (ORCID: ), Serafim Batzoglou [ctb]

Maintainer: Luca De Sano <luca.desano at gmail.com>

Citation (from within R, enter citation("SIMLR")):

Installation

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


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("SIMLR")

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("SIMLR")

Introduction	HTML	R Script
Running SIMLR	HTML	R Script
Reference Manual	PDF
NEWS	Text
LICENSE	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Clustering, GeneExpression, ImmunoOncology, Sequencing, SingleCell, Software
Version	1.33.0
In Bioconductor since	BioC 3.4 (R-3.3) (8 years)
License	file LICENSE
Depends	R (>= 4.1.0)
Imports	parallel, Matrix, stats, methods, Rcpp, pracma, RcppAnnoy, RSpectra
System Requirements
URL	https://github.com/BatzoglouLabSU/SIMLR
Bug Reports	https://github.com/BatzoglouLabSU/SIMLR

Suggests	BiocGenerics, BiocStyle, testthat, knitr, igraph
Linking To	Rcpp
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report	Build Report

Package Archives

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

Source Package	SIMLR_1.33.0.tar.gz
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/SIMLR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/SIMLR
Bioc Package Browser	https://code.bioconductor.org/browse/SIMLR/
Package Short Url	https://bioconductor.org/packages/SIMLR/
Package Downloads Report	Download Stats