Richard J. Sinke

The paper uses allele-specific expression analysis in a large cohort to identify high-impact, autosomal-dominant variants that are compensated by imbalanced expression.

CAPICE is a machine learning method that prioritizes pathogenic variants in exomes, outperforming existing tools for rare and ultra-rare variants.

This paper introduces GADO, a tool that uses gene expression data to predict gene-phenotype associations and improve diagnostic yield in exome sequencing by prioritizing variants in patients with unknown genetic diagnoses.

The paper identifies genetic variants affecting gene expression using genotypes derived from public RNA-seq data, finding cis-eQTLs for 8,034 genes and strong ASE effects for 34 rare pathogenic variants.