OpenGenomeBrowser: a versatile, dataset-independent and scalable web platform for genome data management and comparative genomics

Abstract

Background: As the amount of genomic data continues to grow, there is an increasing need for systematic ways to organize, explore, compare, analyze and share this data. Despite this, there is a lack of suitable platforms to meet this need.

Results: OpenGenomeBrowser is a self-hostable, open-source platform to manage access to genomic data and drastically simplifying comparative genomics analyses. It enables users to interactively generate phylogenetic trees, compare gene loci, browse biochemical pathways, perform gene trait matching, create dot plots, execute BLAST searches, and access the data. It features a flexible user management system, and its modular folder structure enables the organization of genomic data and metadata, and to automate analyses. We tested OpenGenomeBrowser with bacterial, archaeal and yeast genomes. We provide a docker container to make installation and hosting simple. The source code, documentation, tutorials for OpenGenomeBrowser are available at opengenomebrowser.github.io and a demo server is freely accessible at opengenomebrowser.bioinformatics.unibe.ch .

Conclusions: To our knowledge, OpenGenomeBrowser is the first self-hostable, database-independent comparative genome browser. It drastically simplifies commonly used bioinformatics workflows and enables convenient as well as fast data exploration.

Keywords: Comparative genomics; Genome browser; Genome database; Open-source; Self-hosted.

Fig. 1

Schematic diagram of OpenGenomeBrowser. a The user-provided folder structure and metadata files. b The OpenGenomeBrowser software stack in Docker Compose. It consists of a database container (PostgreSQL), a webserver container (nginx), and a container that executes the OpenGenomeBrowser code

Fig. 2

Genomes table. a Sortable and filterable table: Here, one genome is selected, but it is possible to select multiple. b Genome context menu: provides access to other features. c “Show columns and filters”: A click on this bar expands settings to add more metadata columns to the table and apply filters. (⚙) Settings sidebar: Download the table

Fig. 3

Gene comparison. a Input mask for genes to be searched. b Output: alignments. Can be exported in aligned FASTA format. c Output: gene loci. Each subplot shows the genes around one of the queried genes, which are represented as colorful arrows. Orthologous genes have the same colors while genes without orthologs are white. The plots are interactive: pan, zoom, and click on genes. (⚙) Settings sidebar. For alignments: Choose between DNA and the protein sequence alignments, change the alignment method. For gene loci: Set the range around the gene’s locus, change the annotation category by which to color the genes

Fig. 4

Annotation search. a Search for annotations. b Search for genomes. c Coverage matrix output: The numbers in the cells tell the number of genes in the genome that have the annotation. d Clicking on a cell reveals which genes. (⚙) Settings sidebar: Download the table

Fig. 5

Pathway. Visualization of pathway coverage of one or multiple genomes. a Search for pathway maps. b Search for genomes: One or more groups of genomes can be added. In this example, the first group includes all genomes that belong to the taxonomic group Actinobacteria, the second group all Firmicutes. c Output: Coverage visualized on the KEGG citrate cycle pathway. d Color scale: The color of the reaction boxes indicates how many of the selected genomes cover the reaction (white: no genomes, yellow to red: one to all genomes). e Grouping: The left part of each box corresponds to the first group, the right part to the second. In this example, all Actinobacteria genomes (3 out of 3) in the database cover the entire citrate cycle, whereas not all Firmicutes (6 out of 19) do. f Context menu of a reaction box: It shows which annotations are behind the reaction and which genomes cover the reaction. (⚙) Settings sidebar: Change the colors, export the information in the plot as a table, download the pathway map in PNG or SVG format. Copyright permission for publication of this modified image of KEGG pathway map ID 00020 “Citrate cycle (TCA cycle)” (copyright Kanehisa Laboratories) was obtained from Kanehisa Laboratories

Fig. 6

Dot plot. a Search for query and reference genomes. b Output: dot plot. The reference genome is on the X-axis, the query genome on the Y-axis. The genes are shown at the edge of the plot in green and violet, respectively. By default, unique forward alignments are colored in blue, unique reverse alignments in green and repetitive alignments in orange. c Zooming in is achieved by drawing a rectangle with the mouse over a region with repeated elements. d A click on the suspicious gene reveals it to be a transposase. (⚙) Settings sidebar: Configure how the plot is rendered