clustermole: blindly digging for cell types in scRNA-seq clusters

About

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.

The clustermole package provides three primary features:

• cell type prediction based on marker genes
• cell type prediction based on a full expression matrix
• a database of cell type markers

Usage

A vignette is available with usage examples.

Install clustermole from CRAN:

install.packages("clustermole")

Alternatively, you can install the development version from GitHub (not recommended):

BiocManager::install("igordot/clustermole", update = FALSE)

Load clustermole:

library(clustermole)

Perform cell type overrepresentation analysis for a given set of genes:

clustermole_overlaps(genes, species = "hs")

Perform cell type enrichment for a given full gene expression matrix:

clustermole_enrichment(expr_mat, species = "hs")

Retrieve a table of all cell type markers:

clustermole_markers(species = "hs")

Image credit: “A Child’s Primer Of Natural History” by Oliver Herford