Laboratorio de Microbiología Molecular y Biotecnología Ambiental, Departamento de Química & Centro de Biotecnología Daniel Alkalay Lowitt, Universidad Técnica Federico Santa María, Valparaíso, Chile.
Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom.
PLoS Comput Biol. 2023 Apr 4;19(4):e1010998. doi: 10.1371/journal.pcbi.1010998. eCollection 2023 Apr.
The increase in microbial sequenced genomes from pure cultures and metagenomic samples 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) integrates a Cluster of Orthologs Group (COG) categories analysis using DeepNOG, (iii) automatically 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 potential was assessed by analyzing single and multiple genomes of Bacteria and Archaea. Paraburkholderia 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 downloaded from https://github.com/robotoD/GenoVi.
从纯培养物和宏基因组样本中获得的微生物测序基因组数量的增加反映了全基因组和鸟枪法测序方法目前的可达性。然而，用于基因组可视化的软件仍然缺乏自动化、不同分析的集成以及非经验用户的可定制选项。在这项研究中，我们介绍了 GenoVi，这是一个 Python 命令行工具，能够为微生物基因组和序列元素的分析和可视化创建自定义圆形基因组表示。它旨在与完整或草图基因组一起使用，具有可定制的选项，包括 25 种不同的内置调色板（包括 5 种色盲安全调色板）、文本格式选项以及具有多个复制子/序列的完整基因组或序列元素的自动缩放功能。使用 Genbank 格式文件作为输入文件或目录中的多个文件，GenoVi(i)可视化来自 GenBank 注释文件的基因组特征，(ii)使用 DeepNOG 集成 COG（直系同源物组）类别分析，(iii)自动缩放完整基因组或多个序列元素的每个复制子的可视化，(iv)并生成 COG 直方图、COG 频率热图和输出表，包括处理的每个复制子或连续体的一般统计信息。通过分析细菌和古菌的单个和多个基因组来评估 GenoVi 的潜力。分析了 Paraburkholderia 基因组，以快速分类大型多部分基因组中的复制子。GenoVi 作为一个易于使用的命令行工具，提供了可定制的选项，可自动生成用于科学出版物、教育资源和外展活动的基因组图谱。GenoVi 是免费提供的，可以从 https://github.com/robotoD/GenoVi 下载。
