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clustermole  

Unbiased Single-Cell Transcriptomic Data Cell Type Identification
View on CRAN: Click here


Download and install clustermole package within the R console
Install from CRAN:
install.packages("clustermole")

Install from Github:
library("remotes")
install_github("cran/clustermole")

Install by package version:
library("remotes")
install_version("clustermole", "1.1.1")



Attach the package and use:
library("clustermole")
Maintained by
Igor Dolgalev
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-01-20
Latest Update: 2024-01-08
Description:
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.
How to cite:
Igor Dolgalev (2020). clustermole: Unbiased Single-Cell Transcriptomic Data Cell Type Identification. R package version 1.1.1, https://cran.r-project.org/web/packages/clustermole. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:26), 1.0.0 (2020-01-20 11:00), 1.0.1 (2020-01-27 11:00), 1.1.0 (2021-01-26 07:40)
Other packages that cited clustermole R package
View clustermole citation profile
Other R packages that clustermole depends, imports, suggests or enhances
Complete documentation for clustermole
Functions, R codes and Examples using the clustermole R package
Some associated functions: clustermole_enrichment . clustermole_markers . clustermole_overlaps . pipe . read_gmt . 
Some associated R codes: enrichment.R . markers.R . overlaps.R . utils-pipe.R . utils.R .  Full clustermole package functions and examples
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