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>

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

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

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