Journal:DGW: An exploratory data analysis tool for clustering and visualisation of epigenomic marks
| Full article title | DGW: An exploratory data analysis tool for clustering and visualisation of epigenomic marks |
|---|---|
| Journal | BMC Bioinformatics |
| Author(s) | Lukauskas, Saulius; Visintainer, Roberto; Sanguinetti, Guido; Schweikert, Gabriele B. |
| Author affiliation(s) | Imperial College London, Fondazione Bruno Kessler, University of Edinburgh |
| Primary contact | Email: saulius dot lukauskas13 at imperial dot ac dot uk |
| Year published | 2016 |
| Volume and issue | 17(Suppl 16) |
| Page(s) | 447 |
| DOI | 10.1186/s12859-016-1306-0 |
| ISSN | 1471-2105 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1306-0 |
| Download | http://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-016-1306-0 (PDF) |
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Abstract
Background: Functional genomic and epigenomic research relies fundamentally on sequencing-based methods like ChIP-seq for the detection of DNA-protein interactions. These techniques return large, high-dimensional data sets with visually complex structures, such as multi-modal peaks extended over large genomic regions. Current tools for visualisation and data exploration represent and leverage these complex features only to a limited extent.
Results: We present DGW, an open-source software package for simultaneous alignment and clustering of multiple epigenomic marks. DGW uses dynamic time warping to adaptively rescale and align genomic distances which allows to group regions of interest with similar shapes, thereby capturing the structure of epigenomic marks. We demonstrate the effectiveness of the approach in a simulation study and on a real epigenomic data set from the ENCODE project.
Conclusions: Our results show that DGW automatically recognises and aligns important genomic features such as transcription start sites and splicing sites from histone marks. DGW is available as an open-source Python package.
Keywords: Clustering, ChIP-seq, epigenetics, dynamic time warping
References
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.
