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clustermole: Unbiased Single-Cell Transcriptomic Data Cell TypeIdentification

Assignment of cell type labels to single-cell RNA sequencing (scRNA-seq) clusters is often a time-consuming process that involves manual inspection of the cluster marker genes complemented with a detailed literature search. This is especially challenging when unexpected or poorly described populations are present. The clustermole R package provides methods to query thousands of human and mouse cell identity markers sourced from a variety of databases.

Version:1.1.1
Depends:R (≥ 4.3)
Imports:dplyr,GSEABase,GSVA (≥ 1.50.0),magrittr, methods,rlang,singscore,tibble,tidyr, utils
Suggests:covr,knitr,rmarkdown,roxygen2,testthat
Published:2024-01-08
DOI:10.32614/CRAN.package.clustermole
Author:Igor DolgalevORCID iD [aut, cre]
Maintainer:Igor Dolgalev <igor.dolgalev at nyumc.org>
BugReports:https://github.com/igordot/clustermole/issues
License:MIT + fileLICENSE
URL:https://igordot.github.io/clustermole/
NeedsCompilation:no
Materials:README,NEWS
In views:Omics
CRAN checks:clustermole results

Documentation:

Reference manual:clustermole.html ,clustermole.pdf
Vignettes:Introduction to clustermole (source,R code)

Downloads:

Package source: clustermole_1.1.1.tar.gz
Windows binaries: r-devel:clustermole_1.1.1.zip, r-release:clustermole_1.1.1.zip, r-oldrel:clustermole_1.1.1.zip
macOS binaries: r-release (arm64):clustermole_1.1.1.tgz, r-oldrel (arm64):clustermole_1.1.1.tgz, r-release (x86_64):clustermole_1.1.1.tgz, r-oldrel (x86_64):clustermole_1.1.1.tgz
Old sources: clustermole archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=clustermoleto link to this page.


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