Structurally informed evolutionary models improve phylogenetic reconstruction for emerging, seasonal, and pandemic influenza viruses

Xueting Qiu; Justin Bahl

The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/228692 doi: bioRxiv preprint 18 and stepping-stone sampling (SS) (30) were used to compute the marginal likelihood estimation 385 to perform the model selection procedure. PS and SS approaches account for both the number of 386 parameters and the appropriateness of prior distributions for these parameters. 387 The marginal likelihood is the probability of the data (that is, likelihood) given the model The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/228692 doi: bioRxiv preprint 444 data collection and analysis, decision to publish, or preparation of the manuscript. We gratefully 445 acknowledge the authors, originating and submitting laboratories of the sequences from 446 GISAID's EpiFluTM Database, for making tremendous data publicly available and largely 447 benefiting the science community. 448 449 All rights reserved. No reuse allowed without permission.