SIMLR
Single-cell Interpretation via Multi-kernel LeaRning (SIMLR)
Bioconductor version: Release (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("SIMLR")):
Installation
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.
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 | ||
| NEWS | Text | |
| LICENSE | Text |
Details
| 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 |
| Linking To | Rcpp |
| Suggests | BiocGenerics, BiocStyle, testthat, knitr, igraph |
| System Requirements | |
| Enhances | |
| URL | https://github.com/BatzoglouLabSU/SIMLR |
| Bug Reports | https://github.com/BatzoglouLabSU/SIMLR |
See More
| Depends On Me | |
| Imports Me | ccImpute |
| Suggests Me | |
| Links To Me | |
| Build Report |
Package Archives
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 |
| 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 |
| Old Source Packages for BioC 3.17 | Source Archive |