clustermole: Unbiased Single-Cell Transcriptomic Data Cell Type Identification (original) (raw)

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 Dolgalev ORCID iD [aut, cre]
Maintainer: Igor Dolgalev <igor.dolgalev at nyumc.org>
BugReports: https://github.com/igordot/clustermole/issues
License: MIT + file
URL: https://igordot.github.io/clustermole/
NeedsCompilation: no
Materials: README NEWS
In views: Omics
CRAN checks: clustermole results

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