In igordot/clustermole: Unbiased Single-Cell Transcriptomic Data Cell Type Identification

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

We will load clustermole along with dplyr to help with summarizing the data.

library(clustermole)
library(dplyr)

You can use clustermole as a simple database and get a table of all cell type markers.

markers <- clustermole_markers(species = "hs")
markers

Each row contains a gene and a cell type associated with it. The gene column is the gene symbol (human or mouse) and the celltype_full column contains the detailed cell type string including the species and the original database.

Number of cell types

Check the total number of the available cell types.

length(unique(markers$celltype_full))

Number of cell types by source database

Check the source databases and the number of cell types from each.

distinct(markers, celltype_full, db) |> count(db)

Number of cell types by species

Check the number of cell types per species (not available for all cell types).

distinct(markers, celltype_full, species) |> count(species)

Number of cell types by organ

Check the number of available cell types per organ (not available for all cell types).

distinct(markers, celltype_full, organ) |> count(organ, sort = TRUE)

Package version

Check the package version since the database contents may change.

packageVersion("clustermole")

igordot/clustermole documentation built on May 9, 2024, 9:31 p.m.