scDD

DOI: 10.18129/B9.bioc.scDD    

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

Bioconductor version: Release (3.6)

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

Maintainer: Keegan Korthauer <keegan at jimmy.harvard.edu>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("scDD")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("scDD")

 

PDF	R Script	scDD Quickstart
PDF		Reference Manual
Text		NEWS

Details

biocViews	Bayesian, Clustering, DifferentialExpression, MultipleComparison, RNASeq, SingleCell, Software, Visualization
Version	1.2.0
In Bioconductor since	BioC 3.5 (R-3.4) (1 year)
License	GPL-2
Depends	R (>= 3.4)
Imports	fields, mclust, BiocParallel, outliers, ggplot2, EBSeq, arm, SingleCellExperiment, SummarizedExperiment, grDevices, graphics, stats, S4Vectors, scran
LinkingTo
Suggests	BiocStyle, knitr, gridExtra
SystemRequirements
Enhances
URL	https://github.com/kdkorthauer/scDD
BugReports	https://github.com/kdkorthauer/scDD/issues
Depends On Me
Imports Me
Suggests Me	splatter
Build Report

Package Archives

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

Source Package	scDD_1.2.0.tar.gz
Windows Binary	scDD_1.2.0.zip
Mac OS X 10.11 (El Capitan)	scDD_1.2.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/scDD
Package Short Url	http://bioconductor.org/packages/scDD/
Package Downloads Report	Download Stats