Christoph Leuenberger

SweepLink jointly infers demography and linked selection from time-series data, improving detection of selection signals compared to single-locus methods.

This paper introduces birp, a Bayesian tool for testing population trend changes in ecological data, showing it can accurately detect trends even with noisy or sparse data.

The paper introduces TreeSwirl, a method to infer locus-specific mixture proportions from genome-wide allele frequencies, outperforming existing methods in accuracy and sensitivity.

BeXY is a Bayesian method that jointly infers sex chromosome karyotypes and sex-linked scaffolds from low-depth sequencing data, outperforming existing methods in accuracy and power.

The paper extends the F-model to linked loci using a hidden Markov model to detect selection, showing increased statistical power and identifying selection in the human genome.

This paper introduces a method to infer heterozygosity from low coverage genomes, showing it can accurately estimate diversity in ancient samples.

This study shows early European farmers descended directly from Neolithic Aegeans, linking Mediterranean and Central European farmers to southwestern Asia.

This paper introduces a new approximation method for inferring selection and demography from time series genetic data, applied to Influenza virus evolution data.