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

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 v...

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Autores principales: Kultys, Marek, Nicholas, Lydia, Schwarz, Roland, Goldman, Nick, King, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155607/
https://www.ncbi.nlm.nih.gov/pubmed/25237395
http://dx.doi.org/10.1186/1753-6561-8-S2-S8
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author Kultys, Marek
Nicholas, Lydia
Schwarz, Roland
Goldman, Nick
King, James
author_facet Kultys, Marek
Nicholas, Lydia
Schwarz, Roland
Goldman, Nick
King, James
author_sort Kultys, Marek
collection PubMed
description 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.
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spelling pubmed-41556072014-09-18 Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs Kultys, Marek Nicholas, Lydia Schwarz, Roland Goldman, Nick King, James BMC Proc Research 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. BioMed Central 2014-08-28 /pmc/articles/PMC4155607/ /pubmed/25237395 http://dx.doi.org/10.1186/1753-6561-8-S2-S8 Text en Copyright © 2014 Kultys et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Kultys, Marek
Nicholas, Lydia
Schwarz, Roland
Goldman, Nick
King, James
Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs
title Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs
title_full Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs
title_fullStr Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs
title_full_unstemmed Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs
title_short Sequence Bundles: a novel method for visualising, discovering and exploring sequence motifs
title_sort sequence bundles: a novel method for visualising, discovering and exploring sequence motifs
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155607/
https://www.ncbi.nlm.nih.gov/pubmed/25237395
http://dx.doi.org/10.1186/1753-6561-8-S2-S8
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