Academic Journal
Predicted Effector Gene Aggregation, Standards and Unified Schema (PEGASUS): A Community Framework for Effector Gene Reporting.
| Τίτλος: | Predicted Effector Gene Aggregation, Standards and Unified Schema (PEGASUS): A Community Framework for Effector Gene Reporting. |
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| Συγγραφείς: | McMahon A; European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK., Ji Y; European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK., Jurgens JA; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA USA., Costanzo MC; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA USA., Butterworth AS; British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge CB2 0BB, UK.; Department of Public Health and Primary Care, British Heart Foundation Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge CB2 0BB, UK.; NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge CB2 0BB, UK.; Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge CB2 0BB, UK.; Health Data Research UK, Wellcome Genome Campus, University of Cambridge, Hinxton CB10 1RQ, UK., Pahl M; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA., Szyszkowski S; Open Targets, Wellcome Genome Campus, Hinxton, UK.; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK., Heilbron K; Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany.; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.; German Center for Mental Health (DZPG), partner site Berlin/Potsdam, Berlin, Germany.; Bayer AG, Research & Development, Pharmaceuticals, Berlin, Germany., Shiyanbola A; Section of Statistical Multi-omics, Department of Clinical and Experimental Medicine, University of Surrey, UK., Tsepilov Y; Open Targets, Wellcome Genome Campus, Hinxton, UK.; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK., Spracklen CN; Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA USA., Hite D; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA USA., Shilin A; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA USA., Parkinson H; European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK., Burtt N; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA USA., Harris LW; European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK. |
| Συλλογικό Έργο: | PEG Working Group |
| Πηγή: | BioRxiv : the preprint server for biology [bioRxiv] 2026 Jun 17. Date of Electronic Publication: 2026 Jun 17. |
| Τύπος έκδοσης: | Journal Article; Preprint |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE |
| Περίληψη: | Genome-wide association studies (GWAS) increasingly report predicted effector genes (PEGs) - genes hypothesised to mediate the biological effects of associated variants. These function as key outputs for advancing variant-to-function research, mechanistic understanding, and therapeutic discovery. However, the rapid growth of PEG lists has not been matched by standards for organising, annotating, and reporting these predictions. As shown by recent landscape analyses, PEG lists vary widely in methodology, evidence definition, nomenclature, provenance tracking, and data structure, limiting interoperability, benchmarking, reuse, and adherence to FAIR principles. To address this gap, we convened an international multi-stakeholder community comprising method developers, data generators, resource maintainers, curators, funders, journal editors, and downstream users. Through a 2024 workshop and a 2025 working group series, we developed the Predicted Effector Gene Aggregation, Standards and Unified Schema (PEGASUS) framework. PEGASUS specifies (i) a metadata standard to capture provenance, trait and GWAS descriptors, evidence sources, and integration methods; (ii) a structured evidence matrix reporting all genes and all evidence underpinning prioritisation at each locus; and (iii) a concise PEG list that summarises author-prioritised genes linked transparently to underlying evidence. The framework balances transparency, machine readability, burden on submitters, and alignment with existing community standards. PEGASUS provides the first community-developed schema for reporting predicted effector genes and their supporting evidence. Adoption of this framework by authors will improve the comparability, reproducibility, and reusability of PEG outputs across studies, facilitating more robust biological inference, enabling cross-resource comparison of gene-prioritisation methods to support community benchmarking, and integration into downstream resources and analytical pipelines. PEGASUS-compliant data can be shared via the PEG Data Registry platform (https://kpndataregistry.org/peg), promoting re-use and establishing the basis for future integration with publicly shared GWAS data. |
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| Entry Date(s): | Date Created: 20260629 Date Completed: 20260708 Latest Revision: 20260813 |
| Update Code: | 20260814 |
| PubMed Central ID: | PMC13307929 |
| DOI: | 10.64898/2026.06.16.731894 |
| PMID: | 42367912 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 2692-8205 |
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| DOI: | 10.64898/2026.06.16.731894 |