This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see celda.
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>
Citation (from within R,
enter citation("celda")
):
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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("celda")
R Script | Analysis of single-cell genomic data with celda | |
R Script | Estimate and remove cross-contamination from ambient RNA in single-cell data with DecontX | |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
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 |
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 git@git.bioconductor.org:packages/celda |
Package Short Url | https://bioconductor.org/packages/celda/ |
Package Downloads Report | Download Stats |
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