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Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs

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Item Type:Article
Title:Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs
Creators Name:Kultys, M. and Nicholas, L. and Schwarz, R. and Goldman, N. and King, J.
Abstract:Background: We introduce Sequence Bundles--a novel data visualisation method for representing multiple sequence alignments (MSAs). We identify and address key limitations of the existing bioinformatics data visualisation methods (i.e. the Sequence Logo) by enabling Sequence Bundles to give salient visual expression to sequence motifs and other data features, which would otherwise remain hidden. Methods: For the development of Sequence Bundles we employed research-led information design methodologies. Sequences are encoded as uninterrupted, semi-opaque lines plotted on a 2-dimensional reconfigurable grid. Each line represents a single sequence. The thickness and opacity of the stack at each residue in each position indicates the level of conservation and the lines' curved paths expose patterns in correlation and functionality. Several MSAs can be visualised in a composite image. The Sequence Bundles method is designed to favour a tangible, continuous and intuitive display of information. RESULTS We have developed a software demonstration application for generating a Sequence Bundles visualisation of MSAs provided for the BioVis 2013 redesign contest. A subsequent exploration of the visualised line patterns allowed for the discovery of a number of interesting features in the dataset. Reported features include the extreme conservation of sequences displaying a specific residue and bifurcations of the consensus sequence. Conclusions: Sequence Bundles is a novel method for visualisation of MSAs and the discovery of sequence motifs. It can aid in generating new insight and hypothesis making. Sequence Bundles is well disposed for future implementation as an interactive visual analytics software, which can complement existing visualisation tools.
Source:BMC Proceedings
ISSN:1753-6561
Volume:8
Number:Suppl 2
Page Range:S8
Date:28 August 2014
Official Publication:https://doi.org/10.1186/1753-6561-8-S2-S8
PubMed:View item in PubMed

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