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.
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")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("SIMLR")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SIMLR")
R Script | An R Package for todo | |
Reference Manual | ||
Text | LICENSE |
biocViews | Clustering, GeneExpression, Sequencing, SingleCell, Software |
Version | 1.0.1 |
In Bioconductor since | BioC 3.4 (R-3.3) (0.5 years) |
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 |
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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