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

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.

Package details

AuthorKeegan Korthauer [cre, aut] (<>)
Bioconductor views Bayesian Clustering DifferentialExpression ImmunoOncology MultipleComparison RNASeq SingleCell Visualization
MaintainerKeegan Korthauer <>
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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scDD documentation built on Nov. 8, 2020, 7:10 p.m.