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Co-estimation of Phylogeny-aware Alignment and Phylogenetic Tree

Chunxiang Li, Alan Medlar, Ari Löytynoja

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Abstract

The phylogeny-aware alignment algorithm implemented in both PRANK and PAGAN has been found to produce highly accurate alignments for comparative sequence analysis. However, the algorithms reliance on a guide tree during the alignment process can bias the resulting alignment rendering it unsuitable for phylogenetic inference. To overcome these issues, we have developed a new tool, Canopy, for parallelized iterative search of optimal alignment. Using Canopy, we studied the impact of the guide tree as well as the number and relative divergence of sequences on the accuracy of the alignment and inferred phylogeny. We find that PAGAN is the more robust of the two phylogeny-aware alignment methods to errors in the guide tree, but Canopy largely resolves the guide tree-related biases in PRANK. We demonstrate that, for all experimental settings tested, Canopy produces the most accurate sequence alignments and, further, that the inferred phylogenetic trees are of comparable accuracy to those obtained with the leading alternative method, SATe. Our analyses also show that, unlike traditional alignment algorithms, the phylogeny-aware algorithm effectively uses the information from denser sequence sampling and produces more accurate alignments when additional closely-related sequences are included. All methods are available for download at http://wasabiapp.org/software.

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