Afshan Siddiq

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.

This study identifies genetic differences between pediatric and adult cardiomyopathy, finding more constrained variants in childhood cases and female patients.

The paper introduces MuAt, a deep learning model that learns representations of somatic mutations to predict tumour types and subtypes with high accuracy.

The paper introduces DeNovoLOEUF, a method to identify diagnostic variants in genome sequencing data, achieving 96% positive predictive value and uncovering 39 missed diagnoses in the 100,000 Genomes Project.

The paper identifies an intermediate-effect variant in UMOD associated with chronic kidney disease risk and shows it has reduced disease severity compared to canonical ADTKD mutations.

This study uses whole-genome sequencing to identify regulatory and novel genic variants contributing to childhood cardiomyopathy.

The paper identifies gene-specific mutational signatures caused by replication errors and endogenous DNA damage using CRISPR-Cas9 knockouts and whole-genome sequencing.