pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree
Identifieur interne : 000855 ( Main/Exploration ); précédent : 000854; suivant : 000856pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree
Auteurs : Frederick A. Matsen [États-Unis] ; Robin B. Kodner [États-Unis] ; E Virginia Armbrust [États-Unis]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2010.
Abstract
Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-based phylogenetic methods cannot be applied to large volumes of short reads from next-generation sequencing due to computational complexity issues and lack of phylogenetic signal. "Phylogenetic placement," where a reference tree is fixed and the unknown query sequences are placed onto the tree via a reference alignment, is a way to bring the inferential power offered by likelihood-based approaches to large data sets.
This paper introduces
Url:
DOI: 10.1186/1471-2105-11-538
PubMed: 21034504
PubMed Central: 3098090
Affiliations:
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree</title>
<author><name sortKey="Matsen, Frederick A" sort="Matsen, Frederick A" uniqKey="Matsen F" first="Frederick A" last="Matsen">Frederick A. Matsen</name>
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<author><name sortKey="Kodner, Robin B" sort="Kodner, Robin B" uniqKey="Kodner R" first="Robin B" last="Kodner">Robin B. Kodner</name>
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<author><name sortKey="Armbrust, E Virginia" sort="Armbrust, E Virginia" uniqKey="Armbrust E" first="E Virginia" last="Armbrust">E Virginia Armbrust</name>
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<series><title level="j">BMC Bioinformatics</title>
<idno type="eISSN">1471-2105</idno>
<imprint><date when="2010">2010</date>
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-based phylogenetic methods cannot be applied to large volumes of short reads from next-generation sequencing due to computational complexity issues and lack of phylogenetic signal. "Phylogenetic placement," where a reference tree is fixed and the unknown query sequences are placed onto the tree via a reference alignment, is a way to bring the inferential power offered by likelihood-based approaches to large data sets.</p>
</sec>
<sec><title>Results</title>
<p>This paper introduces <monospace>pplacer</monospace>
, a software package for phylogenetic placement and subsequent visualization. The algorithm can place twenty thousand short reads on a reference tree of one thousand taxa per hour per processor, has essentially linear time and memory complexity in the number of reference taxa, and is easy to run in parallel. <monospace>Pplacer</monospace>
features calculation of the posterior probability of a placement on an edge, which is a statistically rigorous way of quantifying uncertainty on an edge-by-edge basis. It also can inform the user of the positional uncertainty for query sequences by calculating expected distance between placement locations, which is crucial in the estimation of uncertainty with a well-sampled reference tree. The software provides visualizations using branch thickness and color to represent number of placements and their uncertainty. A simulation study using reads generated from 631 COG alignments shows a high level of accuracy for phylogenetic placement over a wide range of alignment diversity, and the power of edge uncertainty estimates to measure placement confidence.</p>
</sec>
<sec><title>Conclusions</title>
<p><monospace>Pplacer</monospace>
enables efficient phylogenetic placement and subsequent visualization, making likelihood-based phylogenetics methodology practical for large collections of reads; it is freely available as source code, binaries, and a web service.</p>
</sec>
</div>
</front>
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</TEI>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Washington (État)</li>
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<settlement><li>Seattle</li>
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<orgName><li>Université de Washington</li>
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