Runjun D. Kumar

The paper constructs a high-resolution human pangenome structural variant resource, identifies disease-associated SVs, and demonstrates its utility in filtering variants from probands and associating SVs with traits in a large cohort.

IsoRanker uses long-read transcriptomics to prioritize non-coding variants in Mendelian conditions by detecting expression outliers, allelic imbalance, and NMD, leading to the identification of pathogenic variants in one individual.

The paper recalibrates BAP1 MAVE data for different disease phenotypes to enable accurate variant classification across related disorders.

This study explores patient experiences with genetic variant reclassifications, finding that re-contact practices significantly impact trust and perceived value of genetic testing.

The paper develops TRoLR, a pipeline using long-read sequencing to detect and prioritize pathogenic tandem repeat expansions in diverse populations, identifying known and novel expansions with clinical relevance.

The paper analyzes somatic NMDe variants in oncogenes and dual-function genes across cancer cohorts, identifying two distinct patterns with different functional consequences.

This study identifies barriers to using functional data in clinical variant interpretation and highlights the need for better access and standardized interpretation guidelines.

This study evaluates clinical genome sequencing (GS) over three years at a children's hospital, finding a 35% diagnostic yield and frequent misordering, with higher yields in patients without prior exome sequencing.

This study evaluates the use of clinical exome sequencing in stroke patients, finding a high frequency of Mendelian disorders in a retrospective cohort.

The paper identifies cancer genes by analyzing NMD escape bias in somatic mutations from The Cancer Genome Atlas, finding 29 genes with significant NMD- rates.

The paper identifies somatic mutations with prognostic effects in ER+ breast cancer using genomic data from multiple cohorts.