 
  
 
   
   This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see SIMLR.
Bioconductor version: 3.13
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 [cre, aut]  , Bo Wang [aut], Luca De Sano [aut]
, Bo Wang [aut], Luca De Sano [aut]  , Serafim Batzoglou [ctb]
, 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 "4.1") and enter:
if (!requireNamespace("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")
    
| R Script | Single-cell Interpretation via Multi-kernel LeaRning (\Biocpkg{SIMLR}) | |
| Reference Manual | ||
| Text | NEWS | |
| Text | LICENSE | 
| biocViews | Clustering, GeneExpression, ImmunoOncology, Sequencing, SingleCell, Software | 
| Version | 1.18.0 | 
| In Bioconductor since | BioC 3.4 (R-3.3) (5 years) | 
| License | file LICENSE | 
| Depends | R (>= 4.0.0) | 
| 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 | SingleCellSignalR | 
| Suggests Me | |
| Links To Me | |
| Build Report | 
Follow Installation instructions to use this package in your R session.
| Source Package | SIMLR_1.18.0.tar.gz | 
| Windows Binary | SIMLR_1.18.0.zip (32- & 64-bit) | 
| macOS 10.13 (High Sierra) | SIMLR_1.18.0.tgz | 
| Source Repository | git clone https://git.bioconductor.org/packages/SIMLR | 
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/SIMLR | 
| Package Short Url | https://bioconductor.org/packages/SIMLR/ | 
| Package Downloads Report | Download Stats | 
 
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