Title: Comparing and inferring with trees: from metrics to infectious disease outbreaks and back

Abstract:

Despite the fact that evolution does not always occur in a tree-like way, trees remain a cornerstone of our understanding of genetic variation, from typing data through to whole-genome sequencing data. From long times scales (macroevolutionary data) to very short time scales (infectious disease outbreaks), we use phylogenetic trees to describe genetic variation through time. But the number of possible trees is high, and different data sources and estimation methods produce different trees. Exploring these individually or comparing them pairwise is not always feasible, particularly for large data sets, but we may wish to know whether data support several distinct trees or just one, or we may wish to compare different sets of trees. Here I will describe a suite of tree comparison tools for comparing not only phylogenetic trees, but trees with 'repeated' tip labels, trees at different levels of resolution, and even who-infected-whom (transmission) trees. I will motivate the latter by introducing a method to reconstruct who-infected-whom trees using whole-genome sequence data.