This is the development version of scDDboost; for the stable release version, see scDDboost.
A compositional model to assess expression changes from single-cell rna-seq dataBioconductor version: Development (3.22)
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, entercitation("scDDboost")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("scDDboost")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("scDDboost")Follow Installation instructions to use this package in your R session.
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