Jasper Linthorst

The paper develops a machine learning method to infer DNase1L3 activity from cfDNA fragmentomics, identifying R206C homozygotes with high accuracy and detecting downstream effects of DNase1L3 impairment.

The paper develops an isogenic cell line model to study the effects of the DNASE1L3 p.Arg206Cys variant on cell-free DNA fragmentation and shows how wildtype DNASE1L3 can enrich for mononucleosomal fragments.

This study identifies a common variant in DNASE1L3 that significantly affects cfDNA properties and impacts the accuracy of non-invasive prenatal testing.

The paper predicts VNTRs using a random forest classifier based on long-read sequencing data and validates predictions with short-read pileup analysis across 17 genomes.

CHOP uses haplotype information to efficiently align reads to graph-based reference genomes, improving variation detection in complex datasets.