Søren Besenbacher

This paper introduces BBQ, a tool that improves rare somatic variant calling by modeling sample-specific error rates using overlapping reads, reducing false positives compared to existing tools.

This paper improves ctDNA detection by combining mutation detection with fragmentomic features, achieving higher AUC scores than mutation burden alone.

The paper investigates mutation rates in 43 dog breeds, finding stable rates influenced by parental age and breed-specific differences in mutation accumulation.

The paper introduces ctDNAmer, a reference-free tool for detecting ctDNA from WGS data by analyzing k-mers, showing improved tumor fraction estimation and detection compared to traditional methods.

The paper introduces a method to estimate gene conversion tract length and rate from PacBio HiFi data, showing low visibility of NCO events in human sperm due to low SNV density.

This study uses long-read sequencing to analyze gene conversion and crossover events in human, chimpanzee, and gorilla testes and sperm, revealing species-specific patterns and GC bias in gene conversion.

The paper introduces a method to model mutation rates using k-mer pattern partition, improving prediction of mutation rates and enabling analysis of wider sequence contexts for both point mutations and indels.

This paper uses non-negative matrix factorization to analyze cfDNA fragment length distributions, showing it can infer tumor load, detect cancer, and identify open chromatin-associated signatures.

The paper develops a site-specific model to predict mutation rates in cancer genomes, showing it outperforms regional models by incorporating local genomic variables.

The paper estimates mutation rates in great apes and finds a recent slowdown in the human mutation rate per year compared to other species.