The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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 |
| 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:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=clustermole
to link to this page.
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.
Health stats visible at Monitor.