AskBeacon—performing genomic data exchange and analytics with natural language
Year: 2025
Type: article
Abstract: MOTIVATION: Enabling clinicians and researchers to directly interact with global genomic data resources by removing technological barriers is vital for medical genomics. AskBeacon enables large language models (LLMs) to be applied to securely shared cohorts via the Global Alliance for Genomics and Health Beacon protocol. By simply "asking" Beacon, actionable insights can be gained, analyzed, and made publication-ready. RESULTS: In the Parkinson's Progression Markers Initiative (PPMI), we use natural language to ask whether the sex-differences observed in Parkinson's disease are due to X-linked or autosomal markers. AskBeacon returns a publication-ready visualization showing that for PPMI the autosomal marker occurred 1.4 times more often in males with Parkinson's disease than females, compared to no differences for the X-linked marker. We evaluate commercial and open-weight LLM models, as well as different architectures to identify the best strategy for translating research questions to Beacon queries. AskBeacon implements extensive safety guardrails to ensure that genomic data is not exposed to the LLM directly, and that generated code for data extraction, analysis and visualization process is sanitized and hallucination resistant, so data cannot be leaked or falsified. AVAILABILITY AND IMPLEMENTATION: AskBeacon is available at https://github.com/aehrc/AskBeacon.
Source: Bioinformatics
Authors: Anuradha Wickramarachchi, Shakila Tonni, Sonali Majumdar, Sarvnaz Karimi, Sulev Kõks, Brendan Hosking, Jordi Rambla, Natalie A Twine, Yatish Jain, Denis C Bauer
Institutions: Commonwealth Scientific and Industrial Research Organisation, Australian e-Health Research Centre, Data61, Murdoch University, Perron Institute for Neurological and Translational Science, Universitat Pompeu Fabra, Barcelona Institute of Science and Technology, Centre for Genomic Regulation, Macquarie University, The University of Sydney
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,989
Funders: Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Sanofi, Biogen, Teva Pharmaceutical Industries, Celgene, Jazz Pharmaceuticals, Neurocrine Biosciences, Verily Life Sciences, Voyager Therapeutics, Commonwealth Scientific and Industrial Research Organisation, Servier, H. Lundbeck A/S, Sun Pharma, Genentech, Allergan, Avid Radiopharmaceuticals
OpenAlex ID: W4407851917