A layout framework for genome-wide multiple sequence alignment graphs.

genome analysis genome comparison graph drawing multiple sequence alignment visualization

Journal

Frontiers in bioinformatics
ISSN: 2673-7647
Titre abrégé: Front Bioinform
Pays: Switzerland
ID NLM: 9918227263306676

Informations de publication

Date de publication:
2024
Historique:
received: 19 12 2023
accepted: 08 07 2024
medline: 2 9 2024
pubmed: 2 9 2024
entrez: 2 9 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 39221004
doi: 10.3389/fbinf.2024.1358374
pii: 1358374
pmc: PMC11362851
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1358374

Informations de copyright

Copyright © 2024 Schebera, Zeckzer and Wiegreffe.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Jeremias Schebera (J)

Image and Signal Processing Group, Institute for Computer Science, Leipzig University, Leipzig, Germany.
Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, Leipzig University, Leipzig, Germany.

Dirk Zeckzer (D)

Image and Signal Processing Group, Institute for Computer Science, Leipzig University, Leipzig, Germany.

Daniel Wiegreffe (D)

Image and Signal Processing Group, Institute for Computer Science, Leipzig University, Leipzig, Germany.

Classifications MeSH