Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.

The Multiple Sequence Alignment (MSA) is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history), it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for fi...

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Main Authors: Oscar Westesson, Gerton Lunter, Benedict Paten, Ian Holmes
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22536326/pdf/?tool=EBI
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spelling doaj-3eade5f5b5fa4ed2a190e9ca63d4a7c62021-03-03T20:29:30ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0174e3457210.1371/journal.pone.0034572Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.Oscar WestessonGerton LunterBenedict PatenIan HolmesThe Multiple Sequence Alignment (MSA) is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history), it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for finite substitution models (Dayhoff's probability matrices and Felsenstein's pruning algorithm) to arbitrary-length sequences. In this paper, we report results of a simulation-based benchmark of several methods for reconstruction of indel history. The methods tested include a relatively new algorithm for statistical marginalization of MSAs that sums over a stochastically-sampled ensemble of the most probable evolutionary histories. For mammalian evolutionary parameters on several different trees, the single most likely history sampled by our algorithm appears less biased than histories reconstructed by other MSA methods. The algorithm can also be used for alignment-free inference, where the MSA is explicitly summed out of the analysis. As an illustration of our method, we discuss reconstruction of the evolutionary histories of human protein-coding genes.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22536326/pdf/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Oscar Westesson
Gerton Lunter
Benedict Paten
Ian Holmes
spellingShingle Oscar Westesson
Gerton Lunter
Benedict Paten
Ian Holmes
Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.
PLoS ONE
author_facet Oscar Westesson
Gerton Lunter
Benedict Paten
Ian Holmes
author_sort Oscar Westesson
title Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.
title_short Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.
title_full Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.
title_fullStr Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.
title_full_unstemmed Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.
title_sort accurate reconstruction of insertion-deletion histories by statistical phylogenetics.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2012-01-01
description The Multiple Sequence Alignment (MSA) is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history), it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for finite substitution models (Dayhoff's probability matrices and Felsenstein's pruning algorithm) to arbitrary-length sequences. In this paper, we report results of a simulation-based benchmark of several methods for reconstruction of indel history. The methods tested include a relatively new algorithm for statistical marginalization of MSAs that sums over a stochastically-sampled ensemble of the most probable evolutionary histories. For mammalian evolutionary parameters on several different trees, the single most likely history sampled by our algorithm appears less biased than histories reconstructed by other MSA methods. The algorithm can also be used for alignment-free inference, where the MSA is explicitly summed out of the analysis. As an illustration of our method, we discuss reconstruction of the evolutionary histories of human protein-coding genes.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22536326/pdf/?tool=EBI
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