Previous work has shown that asymmetry in viral phylogenies may be indicative of hetero- geneity in transmission, for example due to acute HIV infection or the presence of ‘core groups’ with higher contact rates. Hence, evidence of asymmetry may provide clues to un- derlying population structure, even when direct information on, for example, stage of infec- tion or contact rates, are missing. However, current tests of phylogenetic asymmetry (a) suffer from false positives when the tips of the phylogeny are sampled at different times and (b) only test for global asymmetry, and hence suffer from false negatives when asymmetry is localised to part of a phylogeny. We present a simple permutation-based approach for testing for asymmetry in a phylogeny, where we compare the observed phylogeny with ran- dom phylogenies with the same sampling and coalescence times, to reduce the false posi- tive rate. We also demonstrate how profiles of measures of asymmetry calculated over a range of evolutionary times in the phylogeny can be used to identify local asymmetry. In combination with different metrics of asymmetry, this combined approach offers detailed in- sights of how phylogenies reconstructed from real viral datasets may deviate from the sim- plistic assumptions of commonly used coalescent and birth-death process models.
Dearlove, B. L., & Frost, S. D. W. (2015). Measuring Asymmetry in Time-Stamped Phylogenies. PLoS Computational Biology, 11(7). https://doi.org/10.1371/journal.pcbi.1004312