FastNet: Fast and accurate inference of phylogenetic networks using large-scale genomic sequence data

Hejase, H.; VandePol, N.; Bonito, G. A.; Liu, K. J.

doi:10.1101/132795

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bioRxiv · 10.1101/132795

FastNet: Fast and accurate inference of phylogenetic networks using large-scale genomic sequence data

Hejase, H.·VandePol, N.·Bonito, G. A.·Liu, K. J.

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Abstract

An emerging discovery in phylogenomics is that interspecific gene flow has played a major role in the evolution of many different organisms. To what extent is the Tree of Life not truly a tree reflecting strict \"vertical\" divergence, but rather a more general graph structure known as a phylogenetic network which also captures \"horizontal\"gene flow? The answer to this fundamental question not only depends upon densely sampled and divergent genomic sequence data, but also compu-tational methods which are capable of accurately and efficiently inferring phylogenetic networks from large-scale genomic sequence datasets. Re-cent methodological advances have attempted to address this gap. How-ever, in the 2016 performance study of Hejase and Liu, state-of-the-art methods fell well short of the scalability requirements of existing phy-logenomic studies.\n\nThe methodological gap remains: how can phylogenetic networks be ac-curately and efficiently inferred using genomic sequence data involving many dozens or hundreds of taxa? In this study, we address this gap by proposing a new phylogenetic divide-and-conquer method which we call FastNet. We conduct a performance study involving a range of evolu-tionary scenarios, and we demonstrate that FastNet outperforms state-of-the-art methods in terms of computational efficiency and topological accuracy.

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Hejase, H., VandePol, N., Bonito, G. A., Liu, K. J.. 2017-05-01. FastNet: Fast and accurate inference of phylogenetic networks using large-scale genomic sequence data. https://doi.org/10.1101/132795

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