scDD

This is the development version of scDD; for the stable release version, see scDD.

Mixture modeling of single-cell RNA-seq data to identify genes with differential distributions


Bioconductor version: Development (3.21)

This package implements a method to analyze single-cell RNA- seq Data utilizing flexible Dirichlet Process mixture models. Genes with differential distributions of expression are classified into several interesting patterns of differences between two conditions. The package also includes functions for simulating data with these patterns from negative binomial distributions.

Author: Keegan Korthauer [cre, aut] (ORCID: )

Maintainer: Keegan Korthauer <keegan at stat.ubc.ca>

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

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("scDD")

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("scDD")
scDD Quickstart PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews Bayesian, Clustering, DifferentialExpression, ImmunoOncology, MultipleComparison, RNASeq, SingleCell, Software, Visualization
Version 1.31.0
In Bioconductor since BioC 3.5 (R-3.4) (7.5 years)
License GPL-2
Depends R (>= 3.5.0)
Imports fields, mclust, BiocParallel, outliers, ggplot2, EBSeq, arm, SingleCellExperiment, SummarizedExperiment, grDevices, graphics, stats, S4Vectors, scran
System Requirements
URL https://github.com/kdkorthauer/scDD
Bug Reports https://github.com/kdkorthauer/scDD/issues
See More
Suggests BiocStyle, knitr, gridExtra
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me splatter
Links To Me
Build Report Build Report

Package Archives

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

Source Package scDD_1.31.0.tar.gz
Windows Binary (x86_64) scDD_1.31.0.zip
macOS Binary (x86_64) scDD_1.31.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/scDD
Source Repository (Developer Access) git clone [email protected]:packages/scDD
Bioc Package Browser https://code.bioconductor.org/browse/scDD/
Package Short Url https://bioconductor.org/packages/scDD/
Package Downloads Report Download Stats