Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
R
 
 
 
 
 
 
man
 
 
src
 
 
 
 
 
 
 
 
 
 

About

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

To install the R package:

# install.packages("devtools")
devtools::install_github("wiscstatman/scDDboost")

A tutorial and examples can be found at Rpackage/vignette/scDDb.pdf.

Paper

Ma, X., Korthauer, K., Kendziorski, C., and Newton, M. A. (2019). A Compositional Model To Assess Expression Changes From Single-Cell RNA-Seq Data. bioRxiv 655795

About

R package for an empirical Bayesian statistical method to detect changes in the distribution of single-cell RNA-Seq data

Resources

Releases

No releases published

Packages

No packages published