Probabilistic phylogenetic inference with insertions and deletions.
Bottom Line:
A fundamental task in sequence analysis is to calculate the probability of a multiple alignment given a phylogenetic tree relating the sequences and an evolutionary model describing how sequences change over time.However, the most widely used phylogenetic models only account for residue substitution events.We apply this model to phylogenetic tree inference by extending the program dnaml in phylip.
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PubMed Central - PubMed
Affiliation: Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America. rivase@janelia.hhmi.org
ABSTRACT
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A fundamental task in sequence analysis is to calculate the probability of a multiple alignment given a phylogenetic tree relating the sequences and an evolutionary model describing how sequences change over time. However, the most widely used phylogenetic models only account for residue substitution events. We describe a probabilistic model of a multiple sequence alignment that accounts for insertion and deletion events in addition to substitutions, given a phylogenetic tree, using a rate matrix augmented by the gap character. Starting from a continuous Markov process, we construct a non-reversible generative (birth-death) evolutionary model for insertions and deletions. The model assumes that insertion and deletion events occur one residue at a time. We apply this model to phylogenetic tree inference by extending the program dnaml in phylip. Using standard benchmarking methods on simulated data and a new "concordance test" benchmark on real ribosomal RNA alignments, we show that the extended program dnamlepsilon improves accuracy relative to the usual approach of ignoring gaps, while retaining the computational efficiency of the Felsenstein peeling algorithm. Related in: MedlinePlus |
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Mentions: Results are summarized in Figure 4. Overall, dnamlε shows tree concordance of 27.9% for SSU and 46.6% for LSU, while dnaml shows tree concordance in 16.9% for SSU and 35.7% for LSU. The error estimate for all these results is about 0.5–0.6%, which indicates that the improvement obtained by dnamlε is significant. LSU alignments are longer than SSU (4205±1179 versus 1959±579), probably explaining the better performance. For alignments with few gaps, the two methods produce similar results. The improvement of dnamlε over dnaml increases with the frequency of gaps in the alignments. |
View Article: PubMed Central - PubMed
Affiliation: Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America. rivase@janelia.hhmi.org