DGEclust: differential expression analysis of clustered count data.
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ABSTRACT:
SUBMITTER: Vavoulis DV
PROVIDER: S-EPMC4365804 | biostudies-other | 2015 Feb
REPOSITORIES: biostudies-other
Publications
DGEclust: differential expression analysis of clustered count data.
Vavoulis Dimitrios V DV Francescatto Margherita M Heutink Peter P Gough Julian J
Genome biology 20150220
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. DGEclust successfully identifies differentially expressed genes under a number of different scenarios, maintaining a low error rate and an excell ...[more]
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