Beacon v2 and Beacon networks: A “lingua franca” for federated data discovery in biomedical genomics, and beyond

Rambla, Jordi; Baudis, Michael; Ariosa, Roberto; Beck, Tim; Fromont, Lauren A.; Navarro, Arcadi; Paloots, Rahel; Rueda, Manuel; Saunders, Gary; Singh, Babita; Spalding, J. Dylan; Törnroos, Juha; Vasallo, Claudia; Veal, Colin; Brookes, Anthony J.

doi:10.1002/humu.24369

Cited by 19 publications

(24 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Beacon is a genomic discovery protocol and data access API issued by the GA4GH. Its most recent version (v2) presented in this issue describes its new and enhanced features for complex queries and richer responses (Rambla et al, 2022). Beacon v2 is designed to sit on top of existing solutions, can be integrated into Beacon networks, and provides a way forward for the next phase of genomic matchmaking and other data queries.…”

Section: Evolution Of Matchmakingmentioning

confidence: 99%

Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking

et al. 2022

View full text Add to dashboard Cite

The Matchmaker Exchange (MME) was launched in 2015 to provide a robust mechanism to discover novel disease-gene relationships. It operates as a federated network connecting databases holding relevant data using a common application programming interface, where two or more users are looking for a match for the same gene (two-sided matchmaking). Seven years from its launch, it is clear that the MME is making outstanding contributions to understanding the morbid anatomy of the genome. The number of unique genes present across the MME has steadily increased over time; there are currently >13,520 unique genes (~68% of all proteincoding genes) connected across the MME's eight genomic matchmaking nodes, GeneMatcher, DECIPHER, PhenomeCentral, MyGene2, seqr, Initiative on Rare and Undiagnosed Disease, PatientMatcher, and the RD-Connect Genome-Phenome Analysis Platform. The collective data set accessible across the MME currently includes more than 120,000 cases from over 12,000 contributors in 98 countries. The discovery of potential new disease-gene relationships is happening daily and international collaborative teams are moving these advances forward to publication, now numbering well over 500. Expansion of data sharing into routine clinical practice by clinicians, genetic counselors, and clinical laboratories has ensured access to discovery for even more individuals with undiagnosed rare genetic diseases. Tens of thousands of patients and their family members have been directly or indirectly impacted by the discoveries facilitated by two-sided genomic matchmaking. MME supports further connections to the literature (PubCaseFinder) and to human and model organism resources (Monarch Initiative) and scientists (ModelMatcher).

show abstract

Section: Evolution Of Matchmakingmentioning

confidence: 99%

Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking

et al. 2022

View full text Add to dashboard Cite

show abstract

“…[13] We show examples of how this can be done in Java and C++ in the main phenopacket schema repository [23] and are preparing a Java library for validation and convenient construction of phenopackets that we will present separately. [24] Additionally, the formats and standards developed for phenopackets are increasingly being adopted by other data discovery and exchange protocols such as the GA4GH Beacon API, [25] as well as several tools and databases that consume or output phenopackets, [26][27][28][29][30][31] thereby promoting a wider penetration of phenopackets standards and practices throughout biomedical research.…”

Section: Discussionmentioning

confidence: 99%

GA4GH Phenopackets: A Practical Introduction

et al. 2022

Self Cite

View full text Add to dashboard Cite

The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases.

show abstract

“…If the markers have been tested in at least one GWAS, and so are shown as being present in GWAS Central, further searches can be undertaken using the GWAS Central REST web service or the website to find more details about the variant, including all phenotypes the variant is associated with. Version 2 of the Beacon API extends the scope of supported queries and responses ( 33 ). Beacon v2.0 requests can include phenotypes and responses can include record details and ‘handovers’ to the native data exchange format.…”

Section: Discussionmentioning

confidence: 99%

GWAS Central: an expanding resource for finding and visualising genotype and phenotype data from genome-wide association studies

Beck

Rowlands

Shorter

et al. 2022

Nucleic Acids Research

View full text Add to dashboard Cite

The GWAS Central resource gathers and curates extensive summary-level genome-wide association study (GWAS) data and puts a range of user-friendly but powerful website tools for the comparison and visualisation of GWAS data at the fingertips of researchers. Through our continued efforts to harmonise and import data received from GWAS authors and consortia, and data sets actively collected from public sources, the database now contains over 72.5 million P-values for over 5000 studies testing over 7.4 million unique genetic markers investigating over 1700 unique phenotypes. Here, we describe an update to integrate this extensive data collection with mouse disease model data to support insights into the functional impact of human genetic variation. GWAS Central has expanded to include mouse gene–phenotype associations observed during mouse gene knockout screens. To allow similar cross-species phenotypes to be compared, terms from mammalian and human phenotype ontologies have been mapped. New interactive interfaces to find, correlate and view human and mouse genotype–phenotype associations are included in the website toolkit. Additionally, the integrated browser for interrogating multiple association data sets has been updated and a GA4GH Beacon API endpoint has been added for discovering variants tested in GWAS. The GWAS Central resource is accessible at https://www.gwascentral.org/.

show abstract

Beacon v2 and Beacon networks: A “lingua franca” for federated data discovery in biomedical genomics, and beyond

Cited by 19 publications

References 26 publications

Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking

Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking

GA4GH Phenopackets: A Practical Introduction

GWAS Central: an expanding resource for finding and visualising genotype and phenotype data from genome-wide association studies

Contact Info

Product

Resources

About