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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2021-06-01
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Online Access: | https://doi.org/10.1177/11779322211021422 |
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doaj-17eadac312be410bb9b1cb5aeb6ed3432021-06-09T02:33:35ZengSAGE PublishingBioinformatics and Biology Insights1177-93222021-06-011510.1177/11779322211021422Unraveling Genome Evolution Throughout Visual Analysis: The XCout PortalSergio Diaz-del-PinoEsteban Perez-WohlfeilOswaldo TrellesDue 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.https://doi.org/10.1177/11779322211021422 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sergio Diaz-del-Pino Esteban Perez-Wohlfeil Oswaldo Trelles |
spellingShingle |
Sergio Diaz-del-Pino Esteban Perez-Wohlfeil Oswaldo Trelles Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal Bioinformatics and Biology Insights |
author_facet |
Sergio Diaz-del-Pino Esteban Perez-Wohlfeil Oswaldo Trelles |
author_sort |
Sergio Diaz-del-Pino |
title |
Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal |
title_short |
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_sort |
unraveling genome evolution throughout visual analysis: the xcout portal |
publisher |
SAGE Publishing |
series |
Bioinformatics and Biology Insights |
issn |
1177-9322 |
publishDate |
2021-06-01 |
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. |
url |
https://doi.org/10.1177/11779322211021422 |
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