Phylogenetic uncertainty and transmission network inference: Lessons from phylogenetic reconciliation

Mukul S. Bansal
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Abstract

The inference of transmission networks from genetic sequence data is an important problem in epidemiology. One approach for building transmission networks is to first reconstruct a phylogenetic tree on the sampled sequences and to then infer transmissions based on this tree. This approach depends crucially on the accuracy of the reconstructed phylogeny and of the transmission inference procedure. However, there is often considerable uncertainty and error in reconstructed phylogenies and significant ambiguity in transmission inference. In this talk, we will introduce a new phylogenetic approach to inferring transmission networks, discuss some of the challenges to the successful implementation of such an approach, and consider some ideas for overcoming these challenges inspired by the literature on phylogenetic reconciliation.
系统发育的不确定性和传递网络推断:来自系统发育调和的教训
从基因序列数据推断传播网络是流行病学中的一个重要问题。构建传输网络的一种方法是首先在采样序列上重建系统发育树,然后根据该树推断传输。这种方法主要取决于重建系统发育和传输推理过程的准确性。然而,在系统发育重建中往往存在相当大的不确定性和误差,在传输推理中也存在明显的模糊性。在这次演讲中,我们将介绍一种新的系统发育方法来推断传输网络,讨论成功实施这种方法所面临的一些挑战,并考虑一些克服这些挑战的想法,这些想法受到系统发育和解文献的启发。
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