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Combining Strengths for Multi-genome Visual Analytics Comparison

The eclosion of data acquisition technologies has shifted the bottleneck in molecular biology research from data acquisition to data analysis. Such is the case in Comparative Genomics, where sequence analysis has transitioned from genes to genomes of several orders of magnitude larger. This fact has...

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Autores principales: Diaz-del-Pino, Sergio, Rodriguez-Brazzarola, Pablo, Perez-Wohlfeil, Esteban, Trelles, Oswaldo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6365554/
https://www.ncbi.nlm.nih.gov/pubmed/30783378
http://dx.doi.org/10.1177/1177932218825127
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author Diaz-del-Pino, Sergio
Rodriguez-Brazzarola, Pablo
Perez-Wohlfeil, Esteban
Trelles, Oswaldo
author_facet Diaz-del-Pino, Sergio
Rodriguez-Brazzarola, Pablo
Perez-Wohlfeil, Esteban
Trelles, Oswaldo
author_sort Diaz-del-Pino, Sergio
collection PubMed
description The eclosion of data acquisition technologies has shifted the bottleneck in molecular biology research from data acquisition to data analysis. Such is the case in Comparative Genomics, where sequence analysis has transitioned from genes to genomes of several orders of magnitude larger. This fact has revealed the need to adapt software to work with huge experiments efficiently and to incorporate new data-analysis strategies to manage results from such studies. In previous works, we presented GECKO, a software to compare large sequences; now we address the representation, browsing, data exploration, and post-processing of the massive amount of information derived from such comparisons. GECKO-MGV is a web-based application organized as client-server architecture. It is aimed at visual analysis of the results from both pairwise and multiple sequences comparison studies combining a set of common commands for image exploration with improved state-of-the-art solutions. In addition, GECKO-MGV integrates different visualization analysis tools while exploiting the concept of layers to display multiple genome comparison datasets. Moreover, the software is endowed with capabilities for contacting external-proprietary and third-party services for further data post-processing and also presents a method to display a timeline of large-scale evolutionary events. As proof-of-concept, we present 2 exercises using bacterial and mammalian genomes which depict the capabilities of GECKO-MGV to perform in-depth, customizable analyses on the fly using web technologies. The first exercise is mainly descriptive and is carried out over bacterial genomes, whereas the second one aims to show the ability to deal with large sequence comparisons. In this case, we display results from the comparison of the first Homo sapiens chromosome against the first 5 chromosomes of Mus musculus.
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spelling pubmed-63655542019-02-19 Combining Strengths for Multi-genome Visual Analytics Comparison Diaz-del-Pino, Sergio Rodriguez-Brazzarola, Pablo Perez-Wohlfeil, Esteban Trelles, Oswaldo Bioinform Biol Insights Original Research The eclosion of data acquisition technologies has shifted the bottleneck in molecular biology research from data acquisition to data analysis. Such is the case in Comparative Genomics, where sequence analysis has transitioned from genes to genomes of several orders of magnitude larger. This fact has revealed the need to adapt software to work with huge experiments efficiently and to incorporate new data-analysis strategies to manage results from such studies. In previous works, we presented GECKO, a software to compare large sequences; now we address the representation, browsing, data exploration, and post-processing of the massive amount of information derived from such comparisons. GECKO-MGV is a web-based application organized as client-server architecture. It is aimed at visual analysis of the results from both pairwise and multiple sequences comparison studies combining a set of common commands for image exploration with improved state-of-the-art solutions. In addition, GECKO-MGV integrates different visualization analysis tools while exploiting the concept of layers to display multiple genome comparison datasets. Moreover, the software is endowed with capabilities for contacting external-proprietary and third-party services for further data post-processing and also presents a method to display a timeline of large-scale evolutionary events. As proof-of-concept, we present 2 exercises using bacterial and mammalian genomes which depict the capabilities of GECKO-MGV to perform in-depth, customizable analyses on the fly using web technologies. The first exercise is mainly descriptive and is carried out over bacterial genomes, whereas the second one aims to show the ability to deal with large sequence comparisons. In this case, we display results from the comparison of the first Homo sapiens chromosome against the first 5 chromosomes of Mus musculus. SAGE Publications 2019-02-01 /pmc/articles/PMC6365554/ /pubmed/30783378 http://dx.doi.org/10.1177/1177932218825127 Text en © The Author(s) 2019 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Diaz-del-Pino, Sergio
Rodriguez-Brazzarola, Pablo
Perez-Wohlfeil, Esteban
Trelles, Oswaldo
Combining Strengths for Multi-genome Visual Analytics Comparison
title Combining Strengths for Multi-genome Visual Analytics Comparison
title_full Combining Strengths for Multi-genome Visual Analytics Comparison
title_fullStr Combining Strengths for Multi-genome Visual Analytics Comparison
title_full_unstemmed Combining Strengths for Multi-genome Visual Analytics Comparison
title_short Combining Strengths for Multi-genome Visual Analytics Comparison
title_sort combining strengths for multi-genome visual analytics comparison
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6365554/
https://www.ncbi.nlm.nih.gov/pubmed/30783378
http://dx.doi.org/10.1177/1177932218825127
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