Anna C. Need

This paper builds a haplotype reference panel from Genomics England data and imputes UK Biobank data, revealing more rare variants and suggesting limitations in detecting rare variant associations with current sample sizes.

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.

This study identifies TMEM63B variants in patients with developmental and epileptic encephalopathy and neurodegeneration, showing altered cation currents and hematological abnormalities.

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 novel Mendelian genes by analyzing mouse embryo lethality and linking them to human disease phenotypes and genetic variants.

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.

This paper identifies potential nootropic drug targets by integrating large-scale cognitive GWAS and transcriptomic data to find credible druggable genes.

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

This study demonstrates that whole genome sequencing can effectively detect repeat expansions in neurological disorders with high sensitivity and specificity, enabling diagnosis in previously undiagnosed patients.

The paper uses pleiotropic meta-analysis to identify genetic loci associated with cognition, education, and schizophrenia, revealing distinct biological mechanisms for concordant and discordant genetic correlations.

This study identifies 206 new genomic loci and 1,041 genes associated with intelligence using a large GWAS meta-analysis of 279,930 individuals.

This study performs a large-scale GWAS of cognitive ability, identifies 70 genomic loci, and finds tissue-specific gene expression and potential drug targets.