Laura Wiseman Harris

PEGASUS defines a community reporting standard for GWAS predicted effector genes: a metadata record, a full locus-by-gene evidence matrix, and a derived author-prioritised gene list.

This paper describes an AI semantics workflow using LLM agents to integrate multimodal biomedical data through ontologies and knowledge graphs.

This paper analyzes 100,526 GWAS to identify pleiotropic genes and their therapeutic implications, finding that highly pleiotropic genes are associated with safety liabilities and that combining PAV support with intermediate pleiotropy improves therapeutic success.

The paper introduces uPheno, a framework for cross-species phenomics integration by harmonizing phenotype data across species and ontologies.

The GWAS Catalog now holds 625,113 curated SNP-trait associations from 6,921 publications plus >85K summary statistics datasets, with a new GWAS-SSF submission standard and GRCh38 harmonisation.

The paper introduces new features and tools for the PGS Catalog to enhance FAIR research, enabling reproducible and equitable polygenic score calculations.

This paper introduces OBA, a formalized ontology for biological attributes to facilitate data integration across phenotypic, genetic, and environmental data.

The paper defines a standard format for GWAS summary statistics to improve data sharing and analysis.

The paper introduces a standardized framework for ancestry data representation in genomics studies and applies it to the NHGRI-EBI GWAS Catalog to improve data integration and analysis.