CelliD

DOI: 10.18129/B9.bioc.CelliD    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see CelliD.

Unbiased Extraction of Single Cell gene signatures using Multiple Correspondence Analysis

Bioconductor version: 3.15

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 institutimagine.org>

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

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("CelliD")

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

Documentation

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

browseVignettes("CelliD")

 

HTML R Script CelliD Vignette
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews ATACSeq, Clustering, DimensionReduction, GeneExpression, GeneSetEnrichment, RNASeq, SingleCell, Software
Version 1.4.0
In Bioconductor since BioC 3.13 (R-4.1) (1.5 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
LinkingTo Rcpp, RcppArmadillo
Suggests knitr, rmarkdown, BiocStyle, testthat, tidyverse, ggpubr, destiny, ggrepel
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package CelliD_1.4.0.tar.gz
Windows Binary CelliD_1.4.0.zip (64-bit only)
macOS Binary (x86_64) CelliD_1.4.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/CelliD
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CelliD
Package Short Url https://bioconductor.org/packages/CelliD/
Package Downloads Report Download Stats

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