celda

DOI: 10.18129/B9.bioc.celda    

This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see celda.

CEllular Latent Dirichlet Allocation

Bioconductor version: 3.12

Utilizing Bayesian hierarchical models to analyze single-cell genomic data.

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

Maintainer: Joshua Campbell <camp at bu.edu>

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("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")

 

PDF	R Script	Analysis of single-cell genomic data with celda
PDF	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, GeneExpression, Sequencing, SingleCell, Software
Version	1.6.1
In Bioconductor since	BioC 3.9 (R-3.6) (2 years)
License	MIT + file LICENSE
Depends	R (>= 3.6)
Imports	plyr, foreach, ggplot2, RColorBrewer, grid, scales, gtable, grDevices, graphics, matrixStats, doParallel, digest, methods, reshape2, MAST, S4Vectors, data.table, Rcpp, RcppEigen, uwot, enrichR, stringi, SummarizedExperiment, MCMCprecision, ggrepel, Rtsne, withr, dendextend, ggdendro, pROC, scater(>= 1.14.4), scran, SingleCellExperiment, dbscan, DelayedArray, Seurat, stringr, Matrix, ComplexHeatmap, multipanelfigure, circlize
LinkingTo	Rcpp, RcppEigen
Suggests	testthat, knitr, roxygen2, rmarkdown, biomaRt, covr, BiocManager, BiocStyle, M3DExampleData, TENxPBMCData
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_1.6.1.tar.gz
Windows Binary	celda_1.6.1.zip (32- & 64-bit)
macOS 10.13 (High Sierra)	celda_1.6.1.tgz
Source Repository	git clone https://git.bioconductor.org/packages/celda
Source Repository (Developer Access)	git clone [email protected]:packages/celda
Package Short Url	https://bioconductor.org/packages/celda/
Package Downloads Report	Download Stats