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Performance, Accuracy, and Web Server for Evolutionary Placement of Short Sequence Reads under Maximum Likelihood

We present an evolutionary placement algorithm (EPA) and a Web server for the rapid assignment of sequence fragments (short reads) to edges of a given phylogenetic tree under the maximum-likelihood model. The accuracy of the algorithm is evaluated on several real-world data sets and compared with pl... Full description

Journal Title: Systematic Biology 2011, Vol.60 (3), p.291-302
Main Author: Berger, Simon A
Other Authors: Krompass, Denis , Stamatakis, Alexandros
Format: Electronic Article Electronic Article
Language: English
Subjects:
Quelle: Alma/SFX Local Collection
Publisher: England: Oxford University Press
ID: ISSN: 1063-5157
Link: https://www.ncbi.nlm.nih.gov/pubmed/21436105
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recordid: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3078422
title: Performance, Accuracy, and Web Server for Evolutionary Placement of Short Sequence Reads under Maximum Likelihood
format: Article
creator:
  • Berger, Simon A
  • Krompass, Denis
  • Stamatakis, Alexandros
subjects:
  • Accuracy
  • Algorithms
  • Amino Acid Sequence
  • Base Sequence
  • Blasts
  • Computer Simulation
  • Databases
  • Datasets
  • Environmental agencies
  • Evolution & development
  • Evolution, Molecular
  • Genetic algorithms
  • Heuristic
  • Heuristics
  • Internet
  • Likelihood Functions
  • Maximum likelihood
  • Maximum likelihood method
  • Metagenomics
  • Nucleotides
  • phylogenetic placement
  • Phylogenetics
  • Phylogeny
  • RAxML
  • Regular
  • Regular Articles
  • Sequence Alignment - methods
  • Sequence Analysis, DNA - methods
  • Sequence Analysis, Protein - methods
  • Sequence Analysis, RNA - methods
  • Sequencing
  • Servers
  • short sequence reads
  • Software
  • Systematic biology
  • Taxa
ispartof: Systematic Biology, 2011, Vol.60 (3), p.291-302
description: We present an evolutionary placement algorithm (EPA) and a Web server for the rapid assignment of sequence fragments (short reads) to edges of a given phylogenetic tree under the maximum-likelihood model. The accuracy of the algorithm is evaluated on several real-world data sets and compared with placement by pair-wise sequence comparison, using edit distances and BLAST. We introduce a slow and accurate as well as a fast and less accurate placement algorithm. For the slow algorithm, we develop additional heuristic techniques that yield almost the same run times as the fast version with only a small loss of accuracy. When those additional heuristics are employed, the run time of the more accurate algorithm is comparable with that of a simple BLAST search for data sets with a high number of short query sequences. Moreover, the accuracy of the EPA is significantly higher, in particular when the sample of taxa in the reference topology is sparse or inadequate. Our algorithm, which has been integrated into RAxML, therefore provides an equally fast but more accurate alternative to BLAST for tree-based inference of the evolutionary origin and composition of short sequence reads. We are also actively developing a Web server that offers a freely available service for computing read placements on trees using the EPA.
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 1063-5157
fulltext: fulltext
issn:
  • 1063-5157
  • 1076-836X
url: Link


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descriptionWe present an evolutionary placement algorithm (EPA) and a Web server for the rapid assignment of sequence fragments (short reads) to edges of a given phylogenetic tree under the maximum-likelihood model. The accuracy of the algorithm is evaluated on several real-world data sets and compared with placement by pair-wise sequence comparison, using edit distances and BLAST. We introduce a slow and accurate as well as a fast and less accurate placement algorithm. For the slow algorithm, we develop additional heuristic techniques that yield almost the same run times as the fast version with only a small loss of accuracy. When those additional heuristics are employed, the run time of the more accurate algorithm is comparable with that of a simple BLAST search for data sets with a high number of short query sequences. Moreover, the accuracy of the EPA is significantly higher, in particular when the sample of taxa in the reference topology is sparse or inadequate. Our algorithm, which has been integrated into RAxML, therefore provides an equally fast but more accurate alternative to BLAST for tree-based inference of the evolutionary origin and composition of short sequence reads. We are also actively developing a Web server that offers a freely available service for computing read placements on trees using the EPA.
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subjectAccuracy ; Algorithms ; Amino Acid Sequence ; Base Sequence ; Blasts ; Computer Simulation ; Databases ; Datasets ; Environmental agencies ; Evolution & development ; Evolution, Molecular ; Genetic algorithms ; Heuristic ; Heuristics ; Internet ; Likelihood Functions ; Maximum likelihood ; Maximum likelihood method ; Metagenomics ; Nucleotides ; phylogenetic placement ; Phylogenetics ; Phylogeny ; RAxML ; Regular ; Regular Articles ; Sequence Alignment - methods ; Sequence Analysis, DNA - methods ; Sequence Analysis, Protein - methods ; Sequence Analysis, RNA - methods ; Sequencing ; Servers ; short sequence reads ; Software ; Systematic biology ; Taxa
ispartofSystematic Biology, 2011, Vol.60 (3), p.291-302
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descriptionWe present an evolutionary placement algorithm (EPA) and a Web server for the rapid assignment of sequence fragments (short reads) to edges of a given phylogenetic tree under the maximum-likelihood model. The accuracy of the algorithm is evaluated on several real-world data sets and compared with placement by pair-wise sequence comparison, using edit distances and BLAST. We introduce a slow and accurate as well as a fast and less accurate placement algorithm. For the slow algorithm, we develop additional heuristic techniques that yield almost the same run times as the fast version with only a small loss of accuracy. When those additional heuristics are employed, the run time of the more accurate algorithm is comparable with that of a simple BLAST search for data sets with a high number of short query sequences. Moreover, the accuracy of the EPA is significantly higher, in particular when the sample of taxa in the reference topology is sparse or inadequate. Our algorithm, which has been integrated into RAxML, therefore provides an equally fast but more accurate alternative to BLAST for tree-based inference of the evolutionary origin and composition of short sequence reads. We are also actively developing a Web server that offers a freely available service for computing read placements on trees using the EPA.
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abstractWe present an evolutionary placement algorithm (EPA) and a Web server for the rapid assignment of sequence fragments (short reads) to edges of a given phylogenetic tree under the maximum-likelihood model. The accuracy of the algorithm is evaluated on several real-world data sets and compared with placement by pair-wise sequence comparison, using edit distances and BLAST. We introduce a slow and accurate as well as a fast and less accurate placement algorithm. For the slow algorithm, we develop additional heuristic techniques that yield almost the same run times as the fast version with only a small loss of accuracy. When those additional heuristics are employed, the run time of the more accurate algorithm is comparable with that of a simple BLAST search for data sets with a high number of short query sequences. Moreover, the accuracy of the EPA is significantly higher, in particular when the sample of taxa in the reference topology is sparse or inadequate. Our algorithm, which has been integrated into RAxML, therefore provides an equally fast but more accurate alternative to BLAST for tree-based inference of the evolutionary origin and composition of short sequence reads. We are also actively developing a Web server that offers a freely available service for computing read placements on trees using the EPA.
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