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RankMap

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

Bioconductor version: 3.24 · Package version: 1.1.2

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.

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
Downloads rank178
Source branchdevel
biocViewsAnnotation, GeneExpression, Preprocessing, Regression, SingleCell, Software, Spatial, Transcriptomics

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageRankMap_1.1.2.tar.gz
Windows binary (x86_64)RankMap_1.1.2.zip
macOS binary (arm64)RankMap_1.1.2.tgz
macOS binary (x86_64)RankMap_1.1.2.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)