schliessen

Filtern

 

Bibliotheken

A Rapid Bootstrap Algorithm for the RAxML Web Servers

Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insuffic... Full description

Journal Title: Systematic biology 2008-10, Vol.57 (5), p.758-771
Main Author: Stamatakis, Alexandros
Other Authors: Hoover, Paul , Rougemont, Jacques
Format: Electronic Article Electronic Article
Language: English
Subjects:
DNA
Quelle: Alma/SFX Local Collection
Publisher: England: Taylor & Francis
ID: ISSN: 1063-5157
Link: https://www.ncbi.nlm.nih.gov/pubmed/18853362
Zum Text:
SendSend as email Add to Book BagAdd to Book Bag
Staff View
recordid: cdi_proquest_miscellaneous_69663729
title: A Rapid Bootstrap Algorithm for the RAxML Web Servers
format: Article
creator:
  • Stamatakis, Alexandros
  • Hoover, Paul
  • Rougemont, Jacques
subjects:
  • Algorithms
  • Amino acids
  • Bioinformatics
  • Bootstrap method
  • Computers
  • Correlations
  • Datasets
  • Deoxyribonucleic acid
  • DNA
  • Evolution, Molecular
  • Genetics
  • Heuristics
  • Inference
  • Internet
  • Likelihood Functions
  • Maximum likelihood
  • Maximum likelihood method
  • phylogenetic inference
  • Phylogenetics
  • Phylogeny
  • Plants - genetics
  • rapid bootstrap
  • RAxML
  • Software
  • support values
  • Taxa
  • Topology
  • Web servers
ispartof: Systematic biology, 2008-10, Vol.57 (5), p.758-771
description: Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets—either with respect to the number of taxa or base pairs—can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBS- and RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources.
language: eng
source: Alma/SFX Local Collection
identifier: ISSN: 1063-5157
fulltext: fulltext
issn:
  • 1063-5157
  • 1076-836X
url: Link


@attributes
NO1
SEARCH_ENGINEprimo_central_multiple_fe
SEARCH_ENGINE_TYPEPrimo Central Search Engine
RANK2.8961186
LOCALfalse
PrimoNMBib
record
control
sourceidjstor_opena
recordidTN_cdi_proquest_miscellaneous_69663729
sourceformatXML
sourcesystemPC
jstor_id27756395
oup_id10.1080/10635150802429642
sourcerecordid27756395
originalsourceidFETCH-LOGICAL-1542t-36e9373091b905531f147e0ddd186e80b79b0823ab687ae791d0d05616eb0ea53
addsrcrecordideNqNkUFv1DAQhSMEoqXwAziAIg6cCHji2I6P24qlSEuR2iJWXCw7mVAv2TjYDpR_j1dZLVKREKcZad58mnkvy54CeQ2kJm-AcMqApbasSsmr8l52DETwoqZ8fX_Xc1okgTjKHoWwIQSAM3iYHUFdM0p5eZyxRX6pR9vmp87FEL0e80X_1Xkbb7Z553webzC_XNx-WOWf0eRX6H-gD4-zB53uAz7Z15Ps0_Lt9dl5sfr47v3ZYlUAq8pYUI6SCkokGEkYo9BBJZC0bQs1x5oYIQ2pS6oNr4VGIaElLWEcOBqCmtGT7GLmuhEHbT2q0dut9r-U01a1A0bVYjuN6men0neqFIyZmpD0HCOmMV3VodHaNFgBJmoCvpyBo3ffJwxRbW1osO_1gG4KikvOqShlEr64I9y4yQ_pWQWyEiL5vRPBLGq8C8FjdzgPiNolpP5KKO0834Mns8X2z8Y-kiQQd6CNjTpaN6R0bP9P9Ku9W8mR_7nk2SzfhOj8YaEUgnEqd-YX89yGiLeHufbfFBdUMHW-_qKuq-X6Yrm6Uqf0N4MOvUs
sourcetypeOpen Access Repository
isCDItrue
recordtypearticle
pqid194774299
display
typearticle
titleA Rapid Bootstrap Algorithm for the RAxML Web Servers
sourceAlma/SFX Local Collection
creatorStamatakis, Alexandros ; Hoover, Paul ; Rougemont, Jacques
contributorRenner, Susanne ; Renner, Susanne
creatorcontribStamatakis, Alexandros ; Hoover, Paul ; Rougemont, Jacques ; Renner, Susanne ; Renner, Susanne
descriptionDespite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets—either with respect to the number of taxa or base pairs—can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBS- and RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources.
identifier
0ISSN: 1063-5157
1EISSN: 1076-836X
2DOI: 10.1080/10635150802429642
3PMID: 18853362
languageeng
publisherEngland: Taylor & Francis
subjectAlgorithms ; Amino acids ; Bioinformatics ; Bootstrap method ; Computers ; Correlations ; Datasets ; Deoxyribonucleic acid ; DNA ; Evolution, Molecular ; Genetics ; Heuristics ; Inference ; Internet ; Likelihood Functions ; Maximum likelihood ; Maximum likelihood method ; phylogenetic inference ; Phylogenetics ; Phylogeny ; Plants - genetics ; rapid bootstrap ; RAxML ; Software ; support values ; Taxa ; Topology ; Web servers
ispartofSystematic biology, 2008-10, Vol.57 (5), p.758-771
rights
0Copyright 2008 Society of Systematic Biologists
12008 Society of Systematic Biologists 2008
lds50peer_reviewed
oafree_for_read
citedbyFETCH-LOGICAL-1542t-36e9373091b905531f147e0ddd186e80b79b0823ab687ae791d0d05616eb0ea53
citesFETCH-LOGICAL-1542t-36e9373091b905531f147e0ddd186e80b79b0823ab687ae791d0d05616eb0ea53
links
openurl$$Topenurl_article
openurlfulltext$$Topenurlfull_article
thumbnail$$Usyndetics_thumb_exl
backlink$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18853362$$D View this record in MEDLINE/PubMed
search
contributor
0Renner, Susanne
1Renner, Susanne
creatorcontrib
0Stamatakis, Alexandros
1Hoover, Paul
2Rougemont, Jacques
title
0A Rapid Bootstrap Algorithm for the RAxML Web Servers
1Systematic biology
addtitleSyst Biol
descriptionDespite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets—either with respect to the number of taxa or base pairs—can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBS- and RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources.
subject
0Algorithms
1Amino acids
2Bioinformatics
3Bootstrap method
4Computers
5Correlations
6Datasets
7Deoxyribonucleic acid
8DNA
9Evolution, Molecular
10Genetics
11Heuristics
12Inference
13Internet
14Likelihood Functions
15Maximum likelihood
16Maximum likelihood method
17phylogenetic inference
18Phylogenetics
19Phylogeny
20Plants - genetics
21rapid bootstrap
22RAxML
23Software
24support values
25Taxa
26Topology
27Web servers
issn
01063-5157
11076-836X
fulltexttrue
rsrctypearticle
creationdate2008
recordtypearticle
recordideNqNkUFv1DAQhSMEoqXwAziAIg6cCHji2I6P24qlSEuR2iJWXCw7mVAv2TjYDpR_j1dZLVKREKcZad58mnkvy54CeQ2kJm-AcMqApbasSsmr8l52DETwoqZ8fX_Xc1okgTjKHoWwIQSAM3iYHUFdM0p5eZyxRX6pR9vmp87FEL0e80X_1Xkbb7Z553webzC_XNx-WOWf0eRX6H-gD4-zB53uAz7Z15Ps0_Lt9dl5sfr47v3ZYlUAq8pYUI6SCkokGEkYo9BBJZC0bQs1x5oYIQ2pS6oNr4VGIaElLWEcOBqCmtGT7GLmuhEHbT2q0dut9r-U01a1A0bVYjuN6men0neqFIyZmpD0HCOmMV3VodHaNFgBJmoCvpyBo3ffJwxRbW1osO_1gG4KikvOqShlEr64I9y4yQ_pWQWyEiL5vRPBLGq8C8FjdzgPiNolpP5KKO0834Mns8X2z8Y-kiQQd6CNjTpaN6R0bP9P9Ku9W8mR_7nk2SzfhOj8YaEUgnEqd-YX89yGiLeHufbfFBdUMHW-_qKuq-X6Yrm6Uqf0N4MOvUs
startdate200810
enddate200810
creator
0Stamatakis, Alexandros
1Hoover, Paul
2Rougemont, Jacques
general
0Taylor & Francis
1Taylor & Francis Group
2Oxford University Press
3Taylor and Francis, Oxford
scope
0BSCLL
1CGR
2CUY
3CVF
4ECM
5EIF
6NPM
7AAYXX
8CITATION
9K9.
107X8
11BOBZL
12CLFQK
sort
creationdate200810
titleA Rapid Bootstrap Algorithm for the RAxML Web Servers
authorStamatakis, Alexandros ; Hoover, Paul ; Rougemont, Jacques
facets
frbrtype5
frbrgroupidcdi_FETCH-LOGICAL-1542t-36e9373091b905531f147e0ddd186e80b79b0823ab687ae791d0d05616eb0ea53
rsrctypearticles
prefilterarticles
languageeng
creationdate2008
topic
0Algorithms
1Amino acids
2Bioinformatics
3Bootstrap method
4Computers
5Correlations
6Datasets
7Deoxyribonucleic acid
8DNA
9Evolution, Molecular
10Genetics
11Heuristics
12Inference
13Internet
14Likelihood Functions
15Maximum likelihood
16Maximum likelihood method
17phylogenetic inference
18Phylogenetics
19Phylogeny
20Plants - genetics
21rapid bootstrap
22RAxML
23Software
24support values
25Taxa
26Topology
27Web servers
toplevel
0peer_reviewed
1online_resources
creatorcontrib
0Stamatakis, Alexandros
1Hoover, Paul
2Rougemont, Jacques
collection
0Istex
1Medline
2MEDLINE
3MEDLINE (Ovid)
4MEDLINE
5MEDLINE
6PubMed
7CrossRef
8ProQuest Health & Medical Complete (Alumni)
9MEDLINE - Academic
10OpenAIRE (Open Access)
11OpenAIRE
jtitleSystematic biology
delivery
delcategoryRemote Search Resource
fulltextfulltext
addata
au
0Stamatakis, Alexandros
1Hoover, Paul
2Rougemont, Jacques
formatjournal
genrearticle
ristypeJOUR
atitleA Rapid Bootstrap Algorithm for the RAxML Web Servers
jtitleSystematic biology
addtitleSyst Biol
date2008-10
risdate2008
volume57
issue5
spage758
epage771
pages758-771
issn1063-5157
eissn1076-836X
abstractDespite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets—either with respect to the number of taxa or base pairs—can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBS- and RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources.
copEngland
pubTaylor & Francis
pmid18853362
doi10.1080/10635150802429642
oafree_for_read