Search

JBrowse and Apollo: Tools for Genome Visualization and Annotation https://github.com/GMOD/jbrowse https://github.com/GMOD/Apollo JBrowse 2: https://github.com/GMOD/jbrowse-components

Introduction: Genome browsers are useful tools for research in human genetics, able to display and integrate biological information such as long and short read sequencing data, variant calls, and annotations. While traditional linear genome browsers have demonstrated broad utility for many applications, there is an increasing need for visualizing complex structural variants (SVs) beyond the linear view. To meet these challenges, we created JBrowse 2: an extensible open-source platform for visualizing and integrating genomic data. Results: JBrowse 2 is a flexible platform that provides the foundation for the development of applications and web dashboards that combine novel views and representations extending beyond linear displays in genomic reference coordinates. For example, a flagship JBrowse 2 application is the SV Inspector, which lets users open a list of structural variants in a data table and see the results in a whole-genome circular view. Clicking on a given variant in the table or circular view opens up a linear view that displays the read evidence supporting the SV, even across complex breakpoints like translocations. Dotplot and synteny views are built-in, enabling “long read vs reference” dotplot visualizations, or alignments of de-novo assembled contigs to the genome. These views are integrated with each other, so that (for example) a long read is just a few clicks away from the corresponding dotplot. In addition to including these new views, the JBrowse 2 platform is designed from the ground up to enable third-party plugins to add new views, data adapters, and track types, which has facilitated the creation of new plugins that address some very specific use cases. These include our MSA view plugin for viewing multiple sequence alignments, data adapters that download data from UCSC and CIVIC APIs, and the Quantseq plugin for viewing quantitative motif scores as a genome browser track. JBrowse 2 is available as both a web app or a local desktop app. We also offer re-usable components on NPM, and users of R can programmatically create an instance of JBrowse 2 with the JBrowseR package on CRAN. JBrowse 2 can also generate high quality SVG snapshots from inside the app, and we also created a CLI tool called jb2export to perform automated or bulk exports of JBrowse 2 visualizations. We anticipate that JBrowse 2 will better serve genome scientists with its structural variant visualization capabilities, and will provide the flexibility to adapt to new visualization and analysis challenges as they emerge in the coming years. Citation Format: Scott Cain, Robin Haw, Caroline Bridge, Junjun Zhang, Robert Buels, Colin Diesh, Garrett Stevens, Teresa Martinez, Peter K. Xie, Elliot Hershberg, Shihab Dider, Lincoln Stein, Ian Holmes. JBrowse 2: An extensible open-source platform for modern genome analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6400.

Motivation Genome browsers are an essential tool in genome analysis. Modern genome browsers enable complex and interactive visualization of a wide variety of genomic data modalities. While such browsers are very powerful, they can be challenging to configure and program for bioinformaticians lacking expertise in web development. Results We have developed an R package that provides an interface to the JBrowse 2 genome browser. The package can be used to configure and customize the browser entirely with R code. The browser can be deployed from the R console, or embedded in Shiny applications or R Markdown documents. Availability and implementation JBrowseR is available for download from CRAN, and the source code is openly available from the Github repository at https://github.com/GMOD/JBrowseR/.

Motivation The CRAM format addresses rising DNA storage costs for short-read sequencing by aligning reads to a reference genome and encoding the resulting alignment with Huffman, subexponential, Elias gamma, rANS, gzip and other codes. The CRAM codec is complex, and until now, there has been no JavaScript implementation. Results We have developed a JavaScript library, Cram-JS, that natively reads and decompresses the CRAM format on-the-fly. The library is used in the JBrowse and IGV-JS genome browsers and can readily be used by other JavaScript applications, in the web browser or in Node. Availability and implementation Cram-JS is written to the ES-6 standard and is available from the GitHub repository at https://github.com/GMOD/cram-js.

Publishing databases in the Resource Description Framework (RDF) model is becoming widely accepted to maximize the syntactic and semantic interoperability of open data in life sciences. Here we report advancements made in the 6th and 7th annual BioHackathons which were held in Tokyo and Miyagi respectively. This review consists of two major sections covering: 1) improvement and utilization of RDF data in various domains of the life sciences and 2) meta-data about these RDF data, the resources that store them, and the service quality of SPARQL Protocol and RDF Query Language (SPARQL) endpoints. The first section describes how we developed RDF data, ontologies and tools in genomics, proteomics, metabolomics, glycomics and by literature text mining. The second section describes how we defined descriptions of datasets, the provenance of data, and quality assessment of services and service discovery. By enhancing the harmonization of these two layers of machine-readable data and knowledge, we improve the way community wide resources are developed and published. Moreover, we outline best practices for the future, and prepare ourselves for an exciting and unanticipatable variety of real world applications in coming years.

The Generic Model Organism Database (GMOD, "http://gmod.org":http://gmod.org) project provides interoperable, open source software tools for managing, visualizing and annotating biological data. GMOD is also a community of people addressing common challenges with biological data. Some well known software in GMOD includes GBrowse and JBrowse for genome browsing, Apollo for genome annotation, Chado for managing data, CMap for comparative map viewing, Galaxy for workflow creation and persistence, and BioMart for warehousing biological data. This talk will focus on three areas of particular interest to iEvoBio participants. 1) GBrowse_syn comparative genomics viewer 2) Natural Diversity Module of the Chado database schema 3) GMOD evolutionary biology hackathon The GBrowse_syn comparative genomics viewer displays synteny between a reference and any number of related species. It shows inversions, duplications, and indels, and can show synteny across non-contiguous regions. It is built on the widely used GBrowse genome viewer. The Natural Diversity Module is an extension to GMOD’s Chado database schema to enable Chado to support natural diversity, population genomics, individuals, breeding, phenotypes and geolocation information. This module is the first extension to Chado to be designed by the community, rather than at one institution. We will close by soliciting nominations and ideas for a GMOD Evolutionary Biology Hackathon. This hackathon will be held November 8-12, at NESCent, which is sponsoring the event. There will be an open call for participation in August.

Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world.

© 2016 Bolleman et al. Background: Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. Description: We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Conclusions: Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.