Joanna Kaplanis

The paper assesses an automated variant prioritisation strategy for genomic newborn screening in the Generation Study, finding that 3-5% of samples require manual review and <1% need confirmatory testing.

This study examines how ancestry and environmental factors influence de novo mutation rates and spectra in a large whole-genome sequenced cohort, finding ancestry-related effects and a link between tobacco smoke exposure and increased mutation rates.

The paper evaluates CNV detection from exome sequencing in the DDD study, finding it has higher sensitivity than low-resolution CMA and comparable sensitivity to exon-resolution CMA.

The paper reports diagnostic outcomes from a large-scale genomic study of developmental disorders, identifying factors that influence diagnostic success.

The paper maps eQTLs during T cell activation and identifies immune disease risk variants that regulate gene expression dynamics, showing colocalization with disease-associated genes.

The paper identifies genetic and chemotherapeutic causes of germline hypermutation by analyzing genome-wide sequences of families with rare genetic diseases.

The paper identifies non-coding variants upstream of MEF2C causing severe developmental disorder through three distinct loss-of-function mechanisms, showing their diagnostic importance in existing exome datasets.

The paper analyzes X-linked coding variation in developmental disorders, finding similar rates in males and females and estimating pathogenicity of inherited variants.

The paper integrates healthcare and research exome sequences to identify 28 novel developmental disorder-associated genes using a simulation-based statistical test.

The paper identifies 299 new genes associated with developmental disorders using exome data from 31,058 trios and finds many more likely remain undiscovered.

The paper compares germline mutation rates and spectra between mice and humans using whole genome sequencing of multi-sibling pedigrees, finding significant differences including a reduced mutation rate in human spermatogonial stem cells.

The paper analyzes de novo mutations in developmental disorders using exome sequencing of 4,293 families, identifying 94 genes and estimating a birth prevalence of 0.22-0.47%.

The paper estimates the contribution of recessive coding variants to developmental disorders using exome data from 7,448 families, finding low prevalence in European ancestry but higher in Pakistani ancestry.

The paper creates a population-scale family tree resource using crowd-sourced genealogy data to study genetic architecture and family dispersion.