Mitchell Shiell, Rosi Bajari, Dusan Andric, Jon Eubank, Brandon F Chan, Anders J Richardsson, Azher Ali, Bashar Allabadi, Yelizar Alturmessov, Jared Baker, Ann Catton, Kim Cullion, Daniel DeMaria, Patrick Dos Santos, Henrich Feher, Francois Gerthoffert, Minh Ha, Robin A Haw, Atul Kachru, Alexandru Lepsa, Alexis Li, Rakesh N Mistry, Hardeep K Nahal-Bose, Aleksandra Pejovic, Samantha Rich, Leonardo Rivera, Ciarán Schütte, Edmund Su, Robert Tisma, Jaser Uddin, Chang Wang, Alex N Wilmer, Linda Xiang, Junjun Zhang, Lincoln D Stein, Vincent Ferretti, Mélanie Courtot, Christina K Yung
{"title":"Overture: an open-source genomics data platform.","authors":"Mitchell Shiell, Rosi Bajari, Dusan Andric, Jon Eubank, Brandon F Chan, Anders J Richardsson, Azher Ali, Bashar Allabadi, Yelizar Alturmessov, Jared Baker, Ann Catton, Kim Cullion, Daniel DeMaria, Patrick Dos Santos, Henrich Feher, Francois Gerthoffert, Minh Ha, Robin A Haw, Atul Kachru, Alexandru Lepsa, Alexis Li, Rakesh N Mistry, Hardeep K Nahal-Bose, Aleksandra Pejovic, Samantha Rich, Leonardo Rivera, Ciarán Schütte, Edmund Su, Robert Tisma, Jaser Uddin, Chang Wang, Alex N Wilmer, Linda Xiang, Junjun Zhang, Lincoln D Stein, Vincent Ferretti, Mélanie Courtot, Christina K Yung","doi":"10.1093/gigascience/giaf038","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Next-generation sequencing has created many new technological challenges in organizing and distributing genomics datasets, which now can routinely reach petabyte scales. Coupled with data-hungry artificial intelligence and machine learning applications, findable, accessible, interoperable, and reusable genomics datasets have never been more valuable. While major archives like the Genomics Data Commons, Sequence Reads Archive, and European Genome-Phenome Archive have improved researchers' ability to share and reuse data, and general-purpose repositories such as Zenodo and Figshare provide valuable platforms for research data publication, the diversity of genomics research precludes any one-size-fits-all approach. In many cases, bespoke solutions are required, and despite funding agencies and journals increasingly mandating reusable data practices, researchers still lack the technical support needed to meet the multifaceted challenges of data reuse.</p><p><strong>Findings: </strong>Overture bridges this gap by providing open-source software for building and deploying customizable genomics data platforms. Its architecture consists of modular microservices, each of which is generalized with narrow responsibilities that together combine to create complete data management systems. These systems enable researchers to organize, share, and explore their genomics data at any scale. Through Overture, researchers can connect their data to both humans and machines, fostering reproducibility and enabling new insights through controlled data sharing and reuse.</p><p><strong>Conclusions: </strong>By making these tools freely available, we can accelerate the development of reliable genomic data management across the research community quickly, flexibly, and at multiple scales. Overture is an open-source project licensed under AGPLv3.0 with all source code publicly available from https://github.com/overture-stack and documentation on development, deployment, and usage available from www.overture.bio.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"14 ","pages":""},"PeriodicalIF":11.8000,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020472/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GigaScience","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/gigascience/giaf038","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Next-generation sequencing has created many new technological challenges in organizing and distributing genomics datasets, which now can routinely reach petabyte scales. Coupled with data-hungry artificial intelligence and machine learning applications, findable, accessible, interoperable, and reusable genomics datasets have never been more valuable. While major archives like the Genomics Data Commons, Sequence Reads Archive, and European Genome-Phenome Archive have improved researchers' ability to share and reuse data, and general-purpose repositories such as Zenodo and Figshare provide valuable platforms for research data publication, the diversity of genomics research precludes any one-size-fits-all approach. In many cases, bespoke solutions are required, and despite funding agencies and journals increasingly mandating reusable data practices, researchers still lack the technical support needed to meet the multifaceted challenges of data reuse.
Findings: Overture bridges this gap by providing open-source software for building and deploying customizable genomics data platforms. Its architecture consists of modular microservices, each of which is generalized with narrow responsibilities that together combine to create complete data management systems. These systems enable researchers to organize, share, and explore their genomics data at any scale. Through Overture, researchers can connect their data to both humans and machines, fostering reproducibility and enabling new insights through controlled data sharing and reuse.
Conclusions: By making these tools freely available, we can accelerate the development of reliable genomic data management across the research community quickly, flexibly, and at multiple scales. Overture is an open-source project licensed under AGPLv3.0 with all source code publicly available from https://github.com/overture-stack and documentation on development, deployment, and usage available from www.overture.bio.
期刊介绍:
GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.