Package: clustermole 1.1.1

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.

Authors:Igor Dolgalev [aut, cre]

clustermole_1.1.1.tar.gz
clustermole_1.1.1.zip(r-4.7)clustermole_1.1.1.zip(r-4.6)clustermole_1.1.1.zip(r-4.5)
clustermole_1.1.1.tgz(r-4.6-any)clustermole_1.1.1.tgz(r-4.5-any)
clustermole_1.1.1.tar.gz(r-4.7-any)clustermole_1.1.1.tar.gz(r-4.6-any)
clustermole_1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
clustermole/json (API)
NEWS

# Install 'clustermole' in R:
install.packages('clustermole', repos = c('https://igordot.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/igordot/clustermole/issues

Pkgdown/docs site:https://igordot.github.io

On CRAN:

Conda:

cell-typecell-type-annotationcell-type-classificationcell-type-identificationcell-type-matchinggene-expression-signaturesscrna-seqsingle-cell

5.47 score 15 stars 39 scripts 427 downloads 5 exports 137 dependencies

Last updated from:f343fa5e2d (on v1.1.1). Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK440
source / vignettesOK345
linux-release-x86_64OK520
macos-release-arm64OK397
macos-oldrel-arm64OK469
windows-develOK371
windows-releaseOK327
windows-oldrelOK332
wasm-releaseOK186

Exports:%>%clustermole_enrichmentclustermole_markersclustermole_overlapsread_gmt

Dependencies:abindannotateAnnotationDbiaskpassassortheadbase64encbeachmatBHBiobaseBiocFileCacheBiocGenericsbiocmakeBiocParallelBiocSingularBiostringsbitbit64blobbslibcachemclicodetoolscpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsdigestdir.expirydplyredgeRevaluatefarverfastmapfilelockfontawesomeformatRfsfutile.loggerfutile.optionsgenericsGenomicRangesggplot2ggrepelgluegraphGSEABaseGSVAgtableh5mreadHDF5Arrayhighrhtmltoolshtmlwidgetshttrhttr2IRangesirlbaisobandjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlaterlatticelazyevallifecyclelimmalocfitmagickmagrittrMatrixMatrixGenericsmatrixStatsmemoisememusemimeopensslotelpillarpkgconfigplotlyplyrpngpromisespurrrR6rappdirsRColorBrewerRcppreshapereshape2rhdf5rhdf5filtersRhdf5librjsonrlangrmarkdownRSQLitersvdS4ArraysS4VectorsS7sassScaledMatrixscalesSeqinfoSingleCellExperimentsingscoresnowSparseArraysparseMatrixStatsSpatialExperimentstatmodstringistringrSummarizedExperimentsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunXMLxtableXVectoryaml

Introduction to clustermole

Rendered fromclustermole-intro.Rmdusingknitr::rmarkdownon Jun 05 2026.

Last update: 2024-01-08
Started: 2020-01-03