DGEclust: differential expression analysis of clustered count data

Abstract

We present a statistical methodology, DGEclust, for differential expression analysis of digital expression data. Our method treats differential expression as a form of clustering, thus unifying these two concepts. Furthermore, it simultaneously addresses the problem of how many clusters are supported by the data and uncertainty in parameter estimation… (More)
DOI: 10.1186/s13059-015-0604-6

Cite this paper

@inproceedings{Vavoulis2015DGEclustDE, title={DGEclust: differential expression analysis of clustered count data}, author={Dimitrios V. Vavoulis and Margherita Francescatto and Peter Heutink and Julian Gough}, booktitle={Genome Biology}, year={2015} }