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")
):
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.
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 |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
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 |
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 |
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