scDDboost
A compositional model to assess expression changes from single-cell rna-seq data
Bioconductor version: 3.23 · Package version: 1.14.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scDDboost")Details
| Maintainer | Xiuyu Ma <watsonforfun@gmail.com> |
| Author | Xiuyu Ma [cre, aut], Michael A. Newton [ctb] |
| License | GPL (>= 2) |
| URL | https://github.com/wiscstatman/scDDboost |
| Bug Reports | https://github.com/wiscstatman/scDDboost/issues |
| System Requirements | c++14 |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Bayesian, Clustering, DifferentialExpression, GeneExpression, Sequencing, SingleCell, Software |
| Package Short Url | https://bioconductor.org/packages/scDDboost/ |
Citation
From within R, enter citation("scDDboost"):
Xiuyu Ma. scDDboost: A compositional model to assess expression changes from single-cell rna-seq data. doi:10.18129/B9.bioc.scDDboost, R package version 1.14.0, https://bioconductor.org/packages/scDDboost.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | scDDboost_1.14.0.tar.gz |
| Windows binary (x86_64) | scDDboost_1.14.0.zip |
| macOS binary (arm64) | scDDboost_1.14.0.tgz |
| macOS binary (x86_64) | scDDboost_1.14.0.tgz |
Dependencies
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