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RankMap

Rank-based reference mapping for fast and robust cell type annotation in spatial and single-cell transcriptomics

Bioconductor version: 3.23 · Package version: 1.0.0

Other Bioconductor versions

devel is the development version; release is the current stable one.

3.24 (devel), 3.23 (release)

RankMap is a fast and scalable tool for reference-based cell type annotation of single-cell and spatial transcriptomics data. It uses ranked gene expression and multinomial regression to achieve robust predictions, even with partial gene coverage. Compatible with Seurat, SingleCellExperiment, and SpatialExperiment objects, RankMap offers flexible preprocessing and significantly faster runtime than tools like SingleR, Azimuth, and RCTD.

DOI: 10.18129/B9.bioc.RankMap

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("RankMap")

Details

MaintainerJinming Cheng <jinming.cheng@outlook.com>
AuthorJinming Cheng [aut, cre] (ORCID: <https://orcid.org/0000-0003-3806-4694>)
LicenseGPL (>= 3)
URLhttps://github.com/jinming-cheng/RankMap
Bug Reportshttps://github.com/jinming-cheng/RankMap/issues
Source branchRELEASE_3_23
Build report Bioconductor build system, r-universe
biocViewsAnnotation, GeneExpression, Preprocessing, Regression, SingleCell, Software, Spatial, Transcriptomics
Package Short Url https://bioconductor.org/packages/RankMap/

Citation

From within R, enter citation("RankMap"):

Jinming Cheng. RankMap: Rank-based reference mapping for fast and robust cell type annotation in spatial and single-cell transcriptomics. doi:10.18129/B9.bioc.RankMap, R package version 1.0.0, https://bioconductor.org/packages/RankMap.

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 packageRankMap_1.0.0.tar.gz
Windows binary (x86_64)RankMap_1.0.0.zip
macOS binary (arm64)RankMap_1.0.0.tgz
macOS binary (x86_64)RankMap_1.0.0.tgz
Dependencies

Depends: R (>= 4.5.0)

Imports: dplyr, glmnet, graphics, magrittr, Matrix, matrixStats, rlang, Seurat, stats, SummarizedExperiment

Suggests: BiocStyle, knitr, rmarkdown, SingleCellExperiment, testthat (>= 3.0.0)