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Co-estimation of Phylogeny-aware Alignment and Phylogenetic Tree
- Publication Year :
- 2016
- Publisher :
- Cold Spring Harbor Laboratory, 2016.
-
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 algorithm’s 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, SATé. 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.
- Subjects :
- 0106 biological sciences
Alternative methods
0303 health sciences
Theoretical computer science
Phylogenetic tree
Sequence analysis
business.industry
Biology
010603 evolutionary biology
01 natural sciences
Rendering (computer graphics)
03 medical and health sciences
Software
Phylogenetics
Iterative search
business
Algorithm
Alignment-free sequence analysis
030304 developmental biology
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....b66792115ffd4b9d6f88510a790b0b72