James John Ashton

The paper uses GenePy scores and clustering to identify genetic clusters in IBD patients, finding NOD2 and NLRP1 as significant drivers with phenotypic associations.

GenePy computes gene-level burden scores using variant data to improve diagnostic strategies for rare diseases through automated, scalable workflows.

This paper applies GenePy2.0 to identify genomic biomarkers in IBD by analyzing GWAS signals and detecting risk/protective variants in large cohorts.

GenePy identifies potential missed biallelic diagnoses in the 100KGP by scoring variants and analyzing phenotypic overlaps, finding 14% of undiagnosed participants may have a missed diagnosis.

GenePy estimates gene-level pathogenicity from whole-exome sequencing data by combining mutational burden and biological impact, demonstrating improved sensitivity in identifying causal genes in common diseases.