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  [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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