Jonathan Shortt

The paper establishes a global consortium to discover rare genetic associations by integrating data from multiple biobanks, identifying 514 gene-trait associations, many detectable only through cross-ancestry meta-analysis.

This paper develops a pipeline for translating type 1 diabetes polygenic risk scores into clinical use, showing they can distinguish type 1 from type 2 diabetes and identify high-risk individuals.

This study calibrates polygenic risk scores (PRS) for African American adults based on genetic ancestry, improving risk stratification and effect estimation for type 2 diabetes and height.

GenoSiS dynamically finds patient-matched cohorts across populations using genotype similarity search to improve clinical analyses.

Admix-kit provides tools for genetic analysis of admixed populations, enabling simulation, association testing, and polygenic scoring.

This study identifies ancestry-specific and sex-specific genetic loci for primary open-angle glaucoma through a meta-analysis of 15 biobanks, highlighting shared biology with vascular mechanisms and cell proliferation.

The paper describes the CCPM Biobank, a dual-purpose genomic resource linking health records and genomic data to support research and clinical applications.

This study evaluates polygenic risk score methods across diverse biobanks and ancestries, finding that European reference panels often yield better performance, while PRS-CS outperforms P+T for high-heritability traits.

This paper shows that meta-analysis fine-mapping is often miscalibrated due to cohort heterogeneity and introduces a QC method to identify suspicious loci.

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

The paper identifies and extends ancient simple sequence repeat-derived regions in the human genome using a kmer-based approach, finding 6.77% of the genome likely derived from SSRs.

SNAPPY assigns Y-chromosome haplogroups using genotype data by evaluating haplotypes in a database and considering phylogenetic support and parsimony.