Improved gene tree error correction in the presence of horizontal gene transfer.

Bioinformatics

Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA, Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge and Broad Institute, Cambridge, MA, USA Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA, Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge and Broad Institute, Cambridge, MA, USA.

Published: April 2015

Motivation: The accurate inference of gene trees is a necessary step in many evolutionary studies. Although the problem of accurate gene tree inference has received considerable attention, most existing methods are only applicable to gene families unaffected by horizontal gene transfer. As a result, the accurate inference of gene trees affected by horizontal gene transfer remains a largely unaddressed problem.

Results: In this study, we introduce a new and highly effective method for gene tree error correction in the presence of horizontal gene transfer. Our method efficiently models horizontal gene transfers, gene duplications and losses, and uses a statistical hypothesis testing framework [Shimodaira-Hasegawa (SH) test] to balance sequence likelihood with topological information from a known species tree. Using a thorough simulation study, we show that existing phylogenetic methods yield inaccurate gene trees when applied to horizontally transferred gene families and that our method dramatically improves gene tree accuracy. We apply our method to a dataset of 11 cyanobacterial species and demonstrate the large impact of gene tree accuracy on downstream evolutionary analyses.

Availability And Implementation: An implementation of our method is available at http://compbio.mit.edu/treefix-dtl/

Contact: : mukul@engr.uconn.edu or manoli@mit.edu

Supplementary Information: Supplementary data are available at Bioinformatics online.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4393519PMC
http://dx.doi.org/10.1093/bioinformatics/btu806DOI Listing

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