GenoVi, an open-source automated circular genome visualizer for bacteria and archaea

Cumsille, Andres; Duran, Roberto; Rodriguez-Delherbe, Andrea; Saona-Urmeneta, Vicente; Camara, Beatriz; Seeger, Michael; Araya, Mauricio; Jara, Nicolas; Buil-Aranda, Carlos; Ioshikhes, Ilya

Abstract

The increase in microbial sequenced genomes from pure cultures and metagenomic sam-ples reflects the current attainability of whole-genome and shotgun sequencing methods. However, software for genome visualization still lacks automation, integration of different analyses, and customizable options for non-experienced users. In this study, we introduce GenoVi, a Python command-line tool able to create custom circular genome representations for the analysis and visualization of microbial genomes and sequence elements. It is designed to work with complete or draft genomes, featuring customizable options including 25 different built-in color palettes (including 5 color-blind safe palettes), text formatting options, and automatic scaling for complete genomes or sequence elements with more than one replicon/sequence. Using a Genbank format file as the input file or multiple files within a directory, GenoVi (i) visualizes genomic features from the GenBank annotation file, (ii) inte-grates a Cluster of Orthologs Group (COG) categories analysis using DeepNOG, (iii) auto-matically scales the visualization of each replicon of complete genomes or multiple sequence elements, (iv) and generates COG histograms, COG frequency heatmaps and output tables including general stats of each replicon or contig processed. GenoVi's poten-tial was assessed by analyzing single and multiple genomes of Bacteria and Archaea. Para-burkholderia genomes were analyzed to obtain a fast classification of replicons in large multipartite genomes. GenoVi works as an easy-to-use command-line tool and provides customizable options to automatically generate genomic maps for scientific publications, educational resources, and outreach activities. GenoVi is freely available and can be down-loaded from https://github.com/robotoD/GenoVi.

Más información

Título según WOS: ID WOS:000964485300003 Not found in local WOS DB
Título de la Revista: PLOS COMPUTATIONAL BIOLOGY
Volumen: 19
Número: 4
Editorial: PUBLIC LIBRARY SCIENCE
Fecha de publicación: 2023
DOI:

10.1371/journal.pcbi.1010998

Notas: ISI