Dominik Schrempf

Distinguishing excess mutations and increased cell death based on variant allele frequencies

The paper develops a method to estimate cell turnover and mutation rates from bulk sequencing data, finding both are elevated in a hepatocellular carcinoma sample.

Scalable empirical mixture models that account for across-site compositional heterogeneity

The paper introduces EDCluster, a scalable method for empirical distribution mixture models that reduces long branch attraction artifacts and improves performance over existing models.

Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity

This paper introduces PoMo, a polymorphism-aware phylogenetic model that improves species tree inference by accounting for polymorphisms and integrates advanced mutation models and rate heterogeneity.

Reversible Polymorphism-Aware Phylogenetic Models and their Application to Tree Inference

This paper introduces revPoMo, a polymorphism-aware phylogenetic model that improves species tree estimation accuracy without increasing runtime with larger sample sizes.

PoMo: An Allele Frequency-based Approach for Species Tree Estimation

PoMo estimates species trees using allele frequencies, outperforming existing methods in accuracy and speed for genome-wide data with incomplete lineage sorting.