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.

README

# clustermole: exploratory scRNA-seq cell type analysis

The clustermole R package (available on [CRAN](https://cran.r-project.org/package=clustermole)) provides methods to query cell identity markers sourced from a variety of databases.
It includes three primary features:

* a meta-database of human and mouse markers for thousands of cell types
* cell type prediction based on a set of marker genes
* cell type prediction based on a table of expression values

Check the [documentation website](https://igordot.github.io/clustermole/) for more information.

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