SIMLR
Single-cell Interpretation via Multi-kernel LeaRning (SIMLR)
Bioconductor version: 3.23 · Package version: 1.38.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SIMLR")Details
| Maintainer | Luca De Sano <luca.desano@gmail.com> |
| Author | Daniele Ramazzotti [aut] (ORCID: <https://orcid.org/0000-0002-6087-2666>), Bo Wang [aut], Luca De Sano [cre, aut] (ORCID: <https://orcid.org/0000-0002-9618-3774>), Serafim Batzoglou [ctb] |
| License | file LICENSE |
| URL | https://github.com/BatzoglouLabSU/SIMLR |
| Bug Reports | https://github.com/BatzoglouLabSU/SIMLR |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Clustering, GeneExpression, ImmunoOncology, Sequencing, SingleCell, Software |
| Package Short Url | https://bioconductor.org/packages/SIMLR/ |
Citation
From within R, enter citation("SIMLR"):
Daniele Ramazzotti, Bo Wang, Luca De Sano. SIMLR: Single-cell Interpretation via Multi-kernel LeaRning (SIMLR). doi:10.18129/B9.bioc.SIMLR, R package version 1.38.0, https://bioconductor.org/packages/SIMLR.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | SIMLR_1.38.0.tar.gz |
| Windows binary (x86_64) | SIMLR_1.38.0.zip |
| macOS binary (arm64) | SIMLR_1.38.0.tgz |
| macOS binary (x86_64) | SIMLR_1.38.0.tgz |