Discrete Distributional Differential Expression (D3E)

D3E is a method for identifying differentially expressed genes from single-cell RNA-seq experiments. D3E compares the full distribution between two sample to identify a set of differentially expressed genes.

[caption id="attachment_104721" align="center" width="1925" class="aligncenter"]Schematic illustration of the transcriptional bursting model and flowchart of D3E[/caption]We have developed Discrece Distributional Differential Expression (D3E), a method for identifying differentially expressed genes. Obtaining a list of genes which are significantly different between two conditions (e.g. mutant vs wild-type or stimulated vs unstimulated) is central to many transcriptome analyses. D3E is specifically designed for single-cell RNA-seq data, and it identifies differentially expressed genes by comparing the full distribution of expression levels for the two conditions rather than just the mean expression. Furthermore, D3E is based on an analytically tractable stochastic model of gene expression. The model facilitates interpretation of the results, and it makes it possible to generate hypotheses about the underlying mechanisms behind the change in gene expression.


D3E is available as a command line tool and can be downloaded from github.

There is also a web-version available for smaller datasets.

Sanger Institute Contributors

Photo of Dr Martin Hemberg, PhD

Dr Martin Hemberg, PhD

CDF Group Leader

External Contributors