biostudies-literatureMuller NFSwiss National Science Foundation17104-17111https://www.ebi.ac.uk/biostudies/studies/S-EPMC7382287biostudies-literatureUnknown117(29)Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment Proceedings of the National Academy of Sciences of the United States of AmericaBayesian inference of reassortment networks reveals fitness benefits of reassortment in human influenza viruses.PMC7382287CR32I3_166258166258Dudas GStadler TStolz UMuller NFVaughan TGfalseBayesian inference of reassortment networks reveals fitness benefits of reassortment in human influenza viruses.Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment 2020-01-01T00:00:00Z2020 Jul2025-04-05T15:19:08.33Z2025-04-05T15:19:08.33ZS-EPMC73822873263198410.1073/pnas.1918304117