This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see SIMLR.
Bioconductor version: 3.17
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] , Bo Wang [aut], Luca De Sano [cre, aut] , Serafim Batzoglou [ctb]
Maintainer: Luca De Sano <luca.desano at gmail.com>
Citation (from within R,
enter citation("SIMLR")
):
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("SIMLR")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SIMLR")
HTML | R Script | Introduction |
HTML | R Script | Running SIMLR |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | Clustering, GeneExpression, ImmunoOncology, Sequencing, SingleCell, Software |
Version | 1.26.1 |
In Bioconductor since | BioC 3.4 (R-3.3) (7 years) |
License | file LICENSE |
Depends | R (>= 4.1.0) |
Imports | parallel, Matrix, stats, methods, Rcpp, pracma, RcppAnnoy, RSpectra |
LinkingTo | Rcpp |
Suggests | BiocGenerics, BiocStyle, testthat, knitr, igraph |
SystemRequirements | |
Enhances | |
URL | https://github.com/BatzoglouLabSU/SIMLR |
BugReports | https://github.com/BatzoglouLabSU/SIMLR |
Depends On Me | |
Imports Me | ccImpute |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | SIMLR_1.26.1.tar.gz |
Windows Binary | SIMLR_1.26.1.zip (64-bit only) |
macOS Binary (x86_64) | SIMLR_1.26.1.tgz |
macOS Binary (arm64) | SIMLR_1.26.1.tgz |
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 |
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