scDDboost

A compositional model to assess expression changes from single-cell rna-seq data


Bioconductor version: Release (3.20)

scDDboost is an R package to analyze changes in the distribution of single-cell expression data between two experimental conditions. Compared to other methods that assess differential expression, scDDboost benefits uniquely from information conveyed by the clustering of cells into cellular subtypes. Through a novel empirical Bayesian formulation it calculates gene-specific posterior probabilities that the marginal expression distribution is the same (or different) between the two conditions. The implementation in scDDboost treats gene-level expression data within each condition as a mixture of negative binomial distributions.

Author: Xiuyu Ma [cre, aut], Michael A. Newton [ctb]

Maintainer: Xiuyu Ma <watsonforfun at gmail.com>

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

Installation

To install this package, start R (version "4.4") and enter:


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

BiocManager::install("scDDboost")

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("scDDboost")
scDDboost Tutorial HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Bayesian, Clustering, DifferentialExpression, GeneExpression, Sequencing, SingleCell, Software
Version 1.8.0
In Bioconductor since BioC 3.16 (R-4.2) (2 years)
License GPL (>= 2)
Depends R (>= 4.2), ggplot2
Imports Rcpp (>= 0.12.11), RcppEigen (>= 0.3.2.9.0), EBSeq, BiocParallel, mclust, SingleCellExperiment, cluster, Oscope, SummarizedExperiment, stats, methods
System Requirements c++11
URL https://github.com/wiscstatman/scDDboost
Bug Reports https://github.com/wiscstatman/scDDboost/issues
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Suggests knitr, rmarkdown, BiocStyle, testthat
Linking To Rcpp, RcppEigen, BH
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Package Archives

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

Source Package scDDboost_1.8.0.tar.gz
Windows Binary (x86_64) scDDboost_1.8.0.zip
macOS Binary (x86_64) scDDboost_1.8.0.tgz
macOS Binary (arm64) scDDboost_1.8.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/scDDboost
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scDDboost
Bioc Package Browser https://code.bioconductor.org/browse/scDDboost/
Package Short Url https://bioconductor.org/packages/scDDboost/
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