celda

DOI: 10.18129/B9.bioc.celda  

CEllular Latent Dirichlet Allocation

Bioconductor version: Release (3.16)

Celda is a suite of Bayesian hierarchical models for clustering single-cell RNA-sequencing (scRNA-seq) data. It is able to perform "bi-clustering" and simultaneously cluster genes into gene modules and cells into cell subpopulations. It also contains DecontX, a novel Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information. A variety of scRNA-seq data visualization functions is also included.

Author: Joshua Campbell [aut, cre], Shiyi Yang [aut], Zhe Wang [aut], Sean Corbett [aut], Yusuke Koga [aut]

Maintainer: Joshua Campbell <camp at bu.edu>

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

Installation

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

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

BiocManager::install("celda")

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("celda")

 

HTML R Script Analysis of single-cell genomic data with celda
HTML R Script Estimate and remove cross-contamination from ambient RNA in single-cell data with DecontX
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews Bayesian, Clustering, DataImport, GeneExpression, ImmunoOncology, Sequencing, SingleCell, Software
Version 1.14.2
In Bioconductor since BioC 3.9 (R-3.6) (4 years)
License MIT + file LICENSE
Depends R (>= 4.0), SingleCellExperiment, Matrix
Imports plyr, foreach, ggplot2, RColorBrewer, grid, scales, gtable, grDevices, graphics, matrixStats, doParallel, digest, methods, reshape2, S4Vectors, data.table, Rcpp, RcppEigen, uwot, enrichR, SummarizedExperiment, MCMCprecision, ggrepel, Rtsne, withr, scater(>= 1.14.4), scran, dbscan, DelayedArray, stringr, ComplexHeatmap, multipanelfigure, circlize
LinkingTo Rcpp, RcppEigen
Suggests testthat, knitr, roxygen2, rmarkdown, biomaRt, covr, BiocManager, BiocStyle, TENxPBMCData, singleCellTK, M3DExampleData
SystemRequirements
Enhances
URL
BugReports https://github.com/campbio/celda/issues
Depends On Me
Imports Me singleCellTK
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package celda_1.14.2.tar.gz
Windows Binary celda_1.14.2.zip (64-bit only)
macOS Binary (x86_64) celda_1.14.2.tgz
macOS Binary (arm64) celda_1.14.2.tgz
Source Repository git clone https://git.bioconductor.org/packages/celda
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/celda
Bioc Package Browser https://code.bioconductor.org/browse/celda/
Package Short Url https://bioconductor.org/packages/celda/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.16 Source Archive

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: