To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SIMLR")

In most cases, you don't need to download the package archive at all.

SIMLR

 

   

SIMLR: Single-cell Interpretation via Multi-kernel LeaRning

Bioconductor version: Release (3.4)

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 to 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. SIMLR is capable of separating known subpopulations more accurately in single-cell data sets than do existing dimension reduction methods. Additionally, SIMLR demonstrates high sensitivity and accuracy on high-throughput peripheral blood mononuclear cells (PBMC) data sets generated by the GemCode single-cell technology from 10x Genomics.

Author: Bo Wang [aut], Daniele Ramazzotti [aut, cre], Luca De Sano [aut], Junjie Zhu [ctb], Emma Pierson [ctb], Serafim Batzoglou [ctb]

Maintainer: Daniele Ramazzotti <daniele.ramazzotti at yahoo.com>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SIMLR")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("SIMLR")

 

PDF R Script An R Package for todo
PDF   Reference Manual
Text   LICENSE

Details

biocViews Clustering, GeneExpression, Sequencing, SingleCell, Software
Version 1.0.1
In Bioconductor since BioC 3.4 (R-3.3) (< 6 months)
License file LICENSE
Depends R (>= 3.3)
Imports parallel, Matrix, stats, methods
LinkingTo
Suggests BiocGenerics, BiocStyle, testthat, knitr, igraph, scran
SystemRequirements
Enhances
URL https://github.com/BatzoglouLabSU/SIMLR
BugReports https://github.com/BatzoglouLabSU/SIMLR
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source SIMLR_1.0.1.tar.gz
Windows Binary SIMLR_1.0.1.zip (32- & 64-bit)
Mac OS X 10.9 (Mavericks) SIMLR_1.0.1.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/SIMLR/tree/release-3.4
Package Short Url http://bioconductor.org/packages/SIMLR/
Package Downloads Report Download Stats

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