NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes

Abstract Summary Large-scale comparative genomic studies have provided important insights into species evolution and diversity, but also lead to a great challenge to visualize. Quick catching or presenting key information hidden in the vast amount of genomic data and relationships among multiple gen...

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Bibliographic Details
Published inBioinformatics (Oxford, England) Vol. 39; no. 3
Main Authors He, Weiming, Yang, Jian, Jing, Yi, Xu, Lian, Yu, Kang, Fang, Xiaodong
Format Journal Article
LanguageEnglish
Published England Oxford University Press 01.03.2023
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Summary:Abstract Summary Large-scale comparative genomic studies have provided important insights into species evolution and diversity, but also lead to a great challenge to visualize. Quick catching or presenting key information hidden in the vast amount of genomic data and relationships among multiple genomes requires an efficient visualization tool. However, current tools for such visualization remain inflexible in layout and/or require advanced computation skills, especially for visualization of genome-based synteny. Here, we developed an easy-to-use and flexible layout tool, NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats. Availability and implementation NGenomeSyn is freely available at GitHub (https://github.com/hewm2008/NGenomeSyn) and Zenodo (https://doi.org/10.5281/zenodo.7645148).
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The authors wish it to be known that, in their opinion, Weiming He and Jian Yang should be regarded as Joint First Authors.
ISSN:1367-4811
1367-4803
1367-4811
DOI:10.1093/bioinformatics/btad121