Charlie F Rowlands

CanVIG-UK evaluates the impact of its activities on variant interpretation in cancer susceptibility genes through a survey, showing high utility and usage of its consensus recommendations.

The paper evaluates how different truthset strategies affect evidence points (EPs) in clinical validation of functional assays across 2,120 gene-truthset-assay combinations.

The paper establishes consensus guidelines for constructing truthsets to validate functional assays in cancer variant interpretation, focusing on missense variants and clinical validation frameworks.

The paper combines enriched case data with population-based case-control analyses using a likelihood-ratio methodology to classify variants in breast cancer susceptibility genes.

CanVar-UK is a web platform that supports collaborative interpretation of germline variants in cancer susceptibility genes by integrating variant data, clinical information, and expert discussions.

The paper evaluates the limitations of existing benign missense variant truthsets for MAVEs and proposes a proactive-systematic framework to improve their construction for better functional evidence classification.

The paper quantifies phenotypic specificity of rare FH variants in HLRCC and renal cancer using likelihood ratios from clinical and population data.

The paper analyzes UK Biobank data to assess the association of APC I1307K variant with colorectal cancer risk in Ashkenazi and non-Ashkenazi whites, finding no significant association and highlighting the need for larger studies.

The paper surveys NHS clinical scientists on their acceptance of MAVE data validation, finding that trusted central bodies are needed for clinical adoption.

This study identifies PRPF8 as essential for left-right organiser cilia function and cardiac asymmetry by regulating ARL13B splicing in mice and zebrafish.

The paper develops a framework for classifying variants of reduced penetrance in cancer susceptibility genes to improve variant interpretation consistency.

The paper introduces PS4-LRCalc, a tool that quantitatively assigns evidence for variant classification using case-control data, enabling continuous scoring instead of dichotomous PS4 scoring.

The paper introduces MRSD, a metric to determine optimal RNA-seq depth and tissue for assessing splicing variants in Mendelian diseases, showing LCLs are best for most gene panels.

This study uses patient-derived iPSCs to model Burn-McKeown Syndrome, revealing reduced TXNL4A expression causes splicing defects and impaired neural crest cell differentiation.

This paper develops an in-silico and functional analysis framework to identify splicing mutations in rare genomic disorders, finding that SpliceAI prioritization improves diagnostic clarity and yield.