clustermole: Unbiased Single-Cell Transcriptomic Data Cell Type Identification

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: 1.1.0
Depends: R (≥ 3.6)
Imports: dplyr, GSEABase, GSVA (≥ 1.26.0), magrittr, methods, rlang (≥ 0.1.2), singscore, tibble, tidyr, utils
Suggests: covr, knitr, prettydoc, rmarkdown, roxygen2, testthat (≥ 2.1.0)
Published: 2021-01-26
Author: Igor Dolgalev [aut, cre]
Maintainer: Igor Dolgalev <igor.dolgalev at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
In views: Omics
CRAN checks: clustermole results


Reference manual: clustermole.pdf
Vignettes: Introduction to clustermole


Package source: clustermole_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): clustermole_1.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): clustermole_1.1.0.tgz
Old sources: clustermole archive


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