{"title":"A layout framework for genome-wide multiple sequence alignment graphs.","authors":"Jeremias Schebera, Dirk Zeckzer, Daniel Wiegreffe","doi":"10.3389/fbinf.2024.1358374","DOIUrl":null,"url":null,"abstract":"<p><p>Sequence alignments are often used to analyze genomic data. However, such alignments are often only calculated and compared on small sequence intervals for analysis purposes. When comparing longer sequences, these are usually divided into shorter sequence intervals for better alignment results. This usually means that the order context of the original sequence is lost. To prevent this, it is possible to use a graph structure to represent the order of the original sequence on the alignment blocks. The visualization of these graph structures can provide insights into the structural variations of genomes in a semi-global context. In this paper, we propose a new graph drawing framework for representing gMSA data. We produce a hierarchical graph layout that supports the comparative analysis of genomes. Based on a reference, the differences and similarities of the different genome orders are visualized. In this work, we present a complete graph drawing framework for gMSA graphs together with the respective algorithms for each of the steps. Additionally, we provide a prototype and an example data set for analyzing gMSA graphs. Based on this data set, we demonstrate the functionalities of the framework using two examples.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1358374"},"PeriodicalIF":2.8000,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362851/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fbinf.2024.1358374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Sequence alignments are often used to analyze genomic data. However, such alignments are often only calculated and compared on small sequence intervals for analysis purposes. When comparing longer sequences, these are usually divided into shorter sequence intervals for better alignment results. This usually means that the order context of the original sequence is lost. To prevent this, it is possible to use a graph structure to represent the order of the original sequence on the alignment blocks. The visualization of these graph structures can provide insights into the structural variations of genomes in a semi-global context. In this paper, we propose a new graph drawing framework for representing gMSA data. We produce a hierarchical graph layout that supports the comparative analysis of genomes. Based on a reference, the differences and similarities of the different genome orders are visualized. In this work, we present a complete graph drawing framework for gMSA graphs together with the respective algorithms for each of the steps. Additionally, we provide a prototype and an example data set for analyzing gMSA graphs. Based on this data set, we demonstrate the functionalities of the framework using two examples.