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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: |
1.1.1 |
| 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 
[aut, cre] |
| Maintainer: |
Igor Dolgalev <igor.dolgalev at nyumc.org> |
| BugReports: |
https://github.com/igordot/clustermole/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://igordot.github.io/clustermole/ |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| In views: |
Omics |
| CRAN checks: |
clustermole results |
Documentation:
Downloads:
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https://CRAN.R-project.org/package=clustermole
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.