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Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal

Due to major breakthroughs in sequencing technologies throughout the last decades, the time and cost per sequencing experiment have reduced drastically, overcoming the data generation barrier during the early genomic era. Such a shift has encouraged the scientific community to develop new computatio...

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Autores principales: Diaz-del-Pino, Sergio, Perez-Wohlfeil, Esteban, Trelles, Oswaldo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191064/
https://www.ncbi.nlm.nih.gov/pubmed/34163150
http://dx.doi.org/10.1177/11779322211021422
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author Diaz-del-Pino, Sergio
Perez-Wohlfeil, Esteban
Trelles, Oswaldo
author_facet Diaz-del-Pino, Sergio
Perez-Wohlfeil, Esteban
Trelles, Oswaldo
author_sort Diaz-del-Pino, Sergio
collection PubMed
description Due to major breakthroughs in sequencing technologies throughout the last decades, the time and cost per sequencing experiment have reduced drastically, overcoming the data generation barrier during the early genomic era. Such a shift has encouraged the scientific community to develop new computational methods that are able to compare large genomic sequences, thus enabling large-scale studies of genome evolution. The field of comparative genomics has proven itself invaluable for studying the evolutionary mechanisms and the forces driving genome evolution. In this line, a full genome comparison study between 2 species requires a quadratic number of comparisons in terms of the number of sequences (around 400 chromosome comparisons in the case of mammalian genomes); however, when studying conserved syntenies or evolutionary rearrangements, many sequence comparisons can be skipped for not all will contain significant signals. Subsequently, the scientific community has developed fast heuristics to perform multiple pairwise comparisons between large sequences to determine whether significant sets of conserved similarities exist. The data generation problem is no longer an issue, yet the limitations have shifted toward the analysis of such massive data. Therefore, we present XCout, a Web-based visual analytics application for multiple genome comparisons designed to improve the analysis of large-scale evolutionary studies using novel techniques in Web visualization. XCout enables to work on hundreds of comparisons at once, thus reducing the time of the analysis by identifying significant signals between chromosomes across multiple species. Among others, XCout introduces several techniques to aid in the analysis of large-scale genome rearrangements, particularly (1) an interactive heatmap interface to display comparisons using automatic color scales based on similarity thresholds to ease detection at first sight, (2) an overlay system to detect individual signal contributions between chromosomes, (3) a tracking tool to trace conserved blocks across different species to perform evolutionary studies, and (4) a search engine to search annotations throughout different species.
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spelling pubmed-81910642021-06-22 Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal Diaz-del-Pino, Sergio Perez-Wohlfeil, Esteban Trelles, Oswaldo Bioinform Biol Insights Original Research Due to major breakthroughs in sequencing technologies throughout the last decades, the time and cost per sequencing experiment have reduced drastically, overcoming the data generation barrier during the early genomic era. Such a shift has encouraged the scientific community to develop new computational methods that are able to compare large genomic sequences, thus enabling large-scale studies of genome evolution. The field of comparative genomics has proven itself invaluable for studying the evolutionary mechanisms and the forces driving genome evolution. In this line, a full genome comparison study between 2 species requires a quadratic number of comparisons in terms of the number of sequences (around 400 chromosome comparisons in the case of mammalian genomes); however, when studying conserved syntenies or evolutionary rearrangements, many sequence comparisons can be skipped for not all will contain significant signals. Subsequently, the scientific community has developed fast heuristics to perform multiple pairwise comparisons between large sequences to determine whether significant sets of conserved similarities exist. The data generation problem is no longer an issue, yet the limitations have shifted toward the analysis of such massive data. Therefore, we present XCout, a Web-based visual analytics application for multiple genome comparisons designed to improve the analysis of large-scale evolutionary studies using novel techniques in Web visualization. XCout enables to work on hundreds of comparisons at once, thus reducing the time of the analysis by identifying significant signals between chromosomes across multiple species. Among others, XCout introduces several techniques to aid in the analysis of large-scale genome rearrangements, particularly (1) an interactive heatmap interface to display comparisons using automatic color scales based on similarity thresholds to ease detection at first sight, (2) an overlay system to detect individual signal contributions between chromosomes, (3) a tracking tool to trace conserved blocks across different species to perform evolutionary studies, and (4) a search engine to search annotations throughout different species. SAGE Publications 2021-06-08 /pmc/articles/PMC8191064/ /pubmed/34163150 http://dx.doi.org/10.1177/11779322211021422 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://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 page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Diaz-del-Pino, Sergio
Perez-Wohlfeil, Esteban
Trelles, Oswaldo
Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal
title Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal
title_full Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal
title_fullStr Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal
title_full_unstemmed Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal
title_short Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal
title_sort unraveling genome evolution throughout visual analysis: the xcout portal
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191064/
https://www.ncbi.nlm.nih.gov/pubmed/34163150
http://dx.doi.org/10.1177/11779322211021422
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