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Unbiased Extraction of Single Cell gene signatures using Multiple Correspondence Analysis

Bioconductor version: Release (3.19)

CelliD is a clustering-free multivariate statistical method for the robust extraction of per-cell gene signatures from single-cell RNA-seq. CelliD allows unbiased cell identity recognition across different donors, tissues-of-origin, model organisms and single-cell omics protocols. The package can also be used to explore functional pathways enrichment in single cell data.

Author: Akira Cortal [aut, cre], Antonio Rausell [aut, ctb]

Maintainer: Akira Cortal <akira.cortal at>

Citation (from within R, enter citation("CelliD")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

CelliD Vignette HTML R Script
Reference Manual PDF


biocViews ATACSeq, Clustering, DimensionReduction, GeneExpression, GeneSetEnrichment, RNASeq, SingleCell, Software
Version 1.12.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-3 + file LICENSE
Depends R (>= 4.1), Seurat (>= 4.0.1), SingleCellExperiment
Imports Rcpp, RcppArmadillo, stats, utils, Matrix, tictoc, scater, stringr, irlba, data.table, glue, pbapply, umap, Rtsne, reticulate, fastmatch, matrixStats, ggplot2, BiocParallel, SummarizedExperiment, fgsea
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Suggests knitr, rmarkdown, BiocStyle, testthat, tidyverse, ggpubr, destiny, ggrepel
Linking To Rcpp, RcppArmadillo
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Follow Installation instructions to use this package in your R session.

Source Package CelliD_1.12.0.tar.gz
Windows Binary
macOS Binary (x86_64) CelliD_1.12.0.tgz
macOS Binary (arm64) CelliD_1.12.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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