Markus J. van Roosmalen

This study evaluates the impact of an individual-specific pangenome on somatic variant calling in a pediatric AML patient, finding reduced false positives and altered phylogenetic branching.

This study uses single-cell whole-genome sequencing to show that Burkitt lymphoma develops through convergent evolution, with early genetic diversity and accelerated mutation accumulation.

The paper develops a method to directly detect 8-oxo-dG using nanopore sequencing by creating synthetic DNA with context variability and training deep learning models.

The paper introduces PTATO, a bioinformatic workflow for detecting somatic mutations in single-cell WGS data using PTA, achieving high sensitivity for base substitutions and indels.

The paper compiles a comprehensive reference dataset of true somatic structural variations by analyzing melanoma and normal cell lines with multiple sequencing technologies and experimental validation.

The paper introduces an updated R/Bioconductor package for analyzing mutational patterns, demonstrating its ability to detect mutational signatures and their biological implications using simulated and real data.

SHARC rapidly identifies somatic genomic structural variations from nanopore sequencing for blood-based cancer monitoring, detecting ten SVs per sample and enabling treatment response tracking in metastatic prostate cancer.

This paper introduces FUDGE, a method for detecting fusion genes using CRISPR/Cas9 enrichment and long-read sequencing, achieving high sensitivity and specificity across various cancer types.

This study prioritizes driver genes in patients with de novo genomic structural variants using integrative analysis of WGS data, phenotype information, and chromatin organization datasets.

This study uses nanopore sequencing to detect and phase structural variants in patient genomes, identifying novel variants missed by short-read sequencing.