DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks

Saulius Lukauskas, Roberto Visintainer, Guido Sanguinetti, Gabriele Schweikert

Research output: Contribution to journalArticlepeer-review

Abstract

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 extend.
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 e↵ectiveness of the approach in a simulation study and on a real epigenomic data set from the ENCODE project. 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 at https://lukauskas.github.com/dgw/.
Original languageEnglish
Number of pages15
JournalBMC Bioinformatics
Volume17
Issue number16
DOIs
Publication statusPublished - 13 Dec 2016

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