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 (3.18)
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]
Maintainer: Keegan Korthauer <keegan at stat.ubc.ca>
citation("scDD")
):
Installation
To install this package, start R (version "4.3") 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 | R Script | |
Reference Manual | ||
NEWS | Text |
Details
biocViews | Bayesian, Clustering, DifferentialExpression, ImmunoOncology, MultipleComparison, RNASeq, SingleCell, Software, Visualization |
Version | 1.25.0 |
In Bioconductor since | BioC 3.5 (R-3.4) (6.5 years) |
License | GPL-2 |
Depends | R (>= 3.5.0) |
Imports | fields, mclust, BiocParallel, outliers, ggplot2, EBSeq, arm, SingleCellExperiment, SummarizedExperiment, grDevices, graphics, stats, S4Vectors, scran |
Linking To | |
Suggests | BiocStyle, knitr, gridExtra |
System Requirements | |
Enhances | |
URL | https://github.com/kdkorthauer/scDD |
Bug Reports | https://github.com/kdkorthauer/scDD/issues |
See More
Depends On Me | |
Imports Me | |
Suggests Me | splatter |
Links To Me | |
Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | scDD_1.25.0.tar.gz |
Windows Binary | scDD_1.25.0.zip (64-bit only) |
macOS Binary (x86_64) | scDD_1.25.0.tgz |
macOS Binary (arm64) | |
Source Repository | git clone https://git.bioconductor.org/packages/scDD |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/scDD |
Bioc Package Browser | https://code.bioconductor.org/browse/scDD/ |
Package Short Url | https://bioconductor.org/packages/scDD/ |
Package Downloads Report | Download Stats |