schliessen

Filtern

 

Bibliotheken

Is BAMM Flawed? Theoretical and Practical Concerns in the Analysis of Multi-Rate Diversification Models

Bayesian analysis of macroevolutionary mixtures (BAMM) is a statistical framework that uses reversible jump Markov chain Monte Carlo to infer complex macroevolutionary dynamics of diversification and phenotypic evolution on phylogenetic trees. A recent article by Moore et al. (MEA) reported a number... Full description

Journal Title: Systematic Biology 2017, Vol.66 (4), p.477-498
Main Author: Rabosky, Daniel L
Other Authors: Mitchell, Jonathan S , Chang, Jonathan
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/28334223
Zum Text:
SendSend as email Add to Book BagAdd to Book Bag
Staff View
recordid: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5790138
title: Is BAMM Flawed? Theoretical and Practical Concerns in the Analysis of Multi-Rate Diversification Models
format: Article
creator:
  • Rabosky, Daniel L
  • Mitchell, Jonathan S
  • Chang, Jonathan
subjects:
  • BAMM
  • Bayes Theorem
  • Bayesian analysis
  • Biodiversity
  • Classification - methods
  • Computer applications
  • Data Interpretation, Statistical
  • diversification
  • Evolution
  • Innovations
  • Likelihood Functions
  • macroevolution
  • Markov analysis
  • Markov chains
  • Mathematical models
  • Models, Biological
  • Monte Carlo simulation
  • Performance assessment
  • Phylogenetics
  • Phylogeny
  • Regular
  • Regular Articles
  • Software
  • speciation
  • Statistical analysis
ispartof: Systematic Biology, 2017, Vol.66 (4), p.477-498
description: Bayesian analysis of macroevolutionary mixtures (BAMM) is a statistical framework that uses reversible jump Markov chain Monte Carlo to infer complex macroevolutionary dynamics of diversification and phenotypic evolution on phylogenetic trees. A recent article by Moore et al. (MEA) reported a number of theoretical and practical concerns with BAMM. Major claims from MEA are that (i) BAMM's likelihood function is incorrect, because it does not account for unobserved rate shifts; (ii) the posterior distribution on the number of rate shifts is overly sensitive to the prior; and (iii) diversification rate estimates from BAMM are unreliable. Here, we show that these and other conclusions from MEA are generally incorrect or unjustified. We first demonstrate that MEA's numerical assessment of the BAMM likelihood is compromised by their use of an invalid likelihood function. We then show that "unobserved rate shifts" appear to be irrelevant for biologically plausible parameterizations of the diversification process. We find that the purportedly extreme prior sensitivity reported by MEA cannot be replicated with standard usage of BAMM v2.5, or with any other version when conventional Bayesian model selection is performed. Finally, we demonstrate that BAMM performs very well at estimating diversification rate variation across the ~20% of simulated trees in MEA's data set for which it is theoretically possible to infer rate shifts with confidence. Due to ascertainment bias, the remaining 80% of their purportedly variable-rate phylogenies are statistically indistinguishable from those produced by a constant-rate birth–death process and were thus poorly suited for the summary statistics used in their performance assessment. We demonstrate that inferences about diversification rates have been accurate and consistent across all major previous releases of the BAMM software. We recognize an acute need to address the theoretical foundations of rate-shift models for phylogenetic trees, and we expect BAMM and other modeling frameworks to improve in response to mathematical and computational innovations. However, we remain optimistic that that the imperfect tools currently available to comparative biologists have provided and will continue to provide important insights into the diversification of life on Earth.
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
RANK2.7823248
LOCALfalse
PrimoNMBib
record
control
sourceidjstor_pubme
recordidTN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5790138
sourceformatXML
sourcesystemPC
jstor_id26408950
sourcerecordid26408950
originalsourceidFETCH-LOGICAL-1517t-ca22d570699d17a376620a971d58a71075ba9dd2bc0907095992da0fc109c2653
addsrcrecordideNp1ks1vFCEYxidGYz_06FFD4sXLKB_L18Vm3Vpt0lVjauKNMMB02czCCkzr_vdSp1bbxNML4fc-vDw8TfMMwdcISvIm73LnYy0_IeEPmn0EOWsFYd8fXq8ZaSmifK85yHkNIUKMosfNHhaEzDAm-83FaQbv5sslOBn0lbNH4HzlYnLFGz0AHSz4krSZdosYjEshAx9AWTkwD3rYZZ9B7MFyHIpvv-riwLG_dCn7vvYUHwNYRuuG_KR51Oshu6c39bD5dvL-fPGxPfv84XQxP2sRRby0RmNsKYdMSou4JpwxDLXkyFKheX0b7bS0FncGSsihpFJiq2FvqhcGM0oOm7eT7nbsNs4aF0rSg9omv9Fpp6L26u5J8Ct1ES8V5RIiIqrAp0kgbl3QPrk7vTa4oqyz41Zd9aoaqjgy2LJezBizhBIsGNW6owJJ3ZGOuCr46maiFH-MLhe18dm4YdDBxTErJATCjFAsK_ryHrqOY6o2V0oyBOt9FFWqnSiTYs7J9bcTIqiuM6GmTKgpE5V_8a8lt_SfEFSA3BM0vvz-vOqQH_4r-3zqWucS019VNoNCUkh-AVJCz0E
sourcetypeOpen Access Repository
isCDItrue
recordtypearticle
pqid1961000151
display
typearticle
titleIs BAMM Flawed? Theoretical and Practical Concerns in the Analysis of Multi-Rate Diversification Models
sourceAlma/SFX Local Collection
creatorRabosky, Daniel L ; Mitchell, Jonathan S ; Chang, Jonathan
creatorcontribRabosky, Daniel L ; Mitchell, Jonathan S ; Chang, Jonathan
descriptionBayesian analysis of macroevolutionary mixtures (BAMM) is a statistical framework that uses reversible jump Markov chain Monte Carlo to infer complex macroevolutionary dynamics of diversification and phenotypic evolution on phylogenetic trees. A recent article by Moore et al. (MEA) reported a number of theoretical and practical concerns with BAMM. Major claims from MEA are that (i) BAMM's likelihood function is incorrect, because it does not account for unobserved rate shifts; (ii) the posterior distribution on the number of rate shifts is overly sensitive to the prior; and (iii) diversification rate estimates from BAMM are unreliable. Here, we show that these and other conclusions from MEA are generally incorrect or unjustified. We first demonstrate that MEA's numerical assessment of the BAMM likelihood is compromised by their use of an invalid likelihood function. We then show that "unobserved rate shifts" appear to be irrelevant for biologically plausible parameterizations of the diversification process. We find that the purportedly extreme prior sensitivity reported by MEA cannot be replicated with standard usage of BAMM v2.5, or with any other version when conventional Bayesian model selection is performed. Finally, we demonstrate that BAMM performs very well at estimating diversification rate variation across the ~20% of simulated trees in MEA's data set for which it is theoretically possible to infer rate shifts with confidence. Due to ascertainment bias, the remaining 80% of their purportedly variable-rate phylogenies are statistically indistinguishable from those produced by a constant-rate birth–death process and were thus poorly suited for the summary statistics used in their performance assessment. We demonstrate that inferences about diversification rates have been accurate and consistent across all major previous releases of the BAMM software. We recognize an acute need to address the theoretical foundations of rate-shift models for phylogenetic trees, and we expect BAMM and other modeling frameworks to improve in response to mathematical and computational innovations. However, we remain optimistic that that the imperfect tools currently available to comparative biologists have provided and will continue to provide important insights into the diversification of life on Earth.
identifier
0ISSN: 1063-5157
1EISSN: 1076-836X
2DOI: 10.1093/sysbio/syx037
3PMID: 28334223
languageeng
publisherEngland: Oxford University Press
subjectBAMM ; Bayes Theorem ; Bayesian analysis ; Biodiversity ; Classification - methods ; Computer applications ; Data Interpretation, Statistical ; diversification ; Evolution ; Innovations ; Likelihood Functions ; macroevolution ; Markov analysis ; Markov chains ; Mathematical models ; Models, Biological ; Monte Carlo simulation ; Performance assessment ; Phylogenetics ; Phylogeny ; Regular ; Regular Articles ; Software ; speciation ; Statistical analysis
ispartofSystematic Biology, 2017, Vol.66 (4), p.477-498
rights
0Copyright © 2017 Society of Systematic Biologists
1The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
2Copyright Oxford University Press, UK Jul 2017
3The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. 2017
lds50peer_reviewed
oafree_for_read
citedbyFETCH-LOGICAL-1517t-ca22d570699d17a376620a971d58a71075ba9dd2bc0907095992da0fc109c2653
citesFETCH-LOGICAL-1517t-ca22d570699d17a376620a971d58a71075ba9dd2bc0907095992da0fc109c2653
links
openurl$$Topenurl_article
openurlfulltext$$Topenurlfull_article
thumbnail$$Usyndetics_thumb_exl
backlink$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28334223$$D View this record in MEDLINE/PubMed
search
creatorcontrib
0Rabosky, Daniel L
1Mitchell, Jonathan S
2Chang, Jonathan
title
0Is BAMM Flawed? Theoretical and Practical Concerns in the Analysis of Multi-Rate Diversification Models
1Systematic Biology
addtitleSyst Biol
descriptionBayesian analysis of macroevolutionary mixtures (BAMM) is a statistical framework that uses reversible jump Markov chain Monte Carlo to infer complex macroevolutionary dynamics of diversification and phenotypic evolution on phylogenetic trees. A recent article by Moore et al. (MEA) reported a number of theoretical and practical concerns with BAMM. Major claims from MEA are that (i) BAMM's likelihood function is incorrect, because it does not account for unobserved rate shifts; (ii) the posterior distribution on the number of rate shifts is overly sensitive to the prior; and (iii) diversification rate estimates from BAMM are unreliable. Here, we show that these and other conclusions from MEA are generally incorrect or unjustified. We first demonstrate that MEA's numerical assessment of the BAMM likelihood is compromised by their use of an invalid likelihood function. We then show that "unobserved rate shifts" appear to be irrelevant for biologically plausible parameterizations of the diversification process. We find that the purportedly extreme prior sensitivity reported by MEA cannot be replicated with standard usage of BAMM v2.5, or with any other version when conventional Bayesian model selection is performed. Finally, we demonstrate that BAMM performs very well at estimating diversification rate variation across the ~20% of simulated trees in MEA's data set for which it is theoretically possible to infer rate shifts with confidence. Due to ascertainment bias, the remaining 80% of their purportedly variable-rate phylogenies are statistically indistinguishable from those produced by a constant-rate birth–death process and were thus poorly suited for the summary statistics used in their performance assessment. We demonstrate that inferences about diversification rates have been accurate and consistent across all major previous releases of the BAMM software. We recognize an acute need to address the theoretical foundations of rate-shift models for phylogenetic trees, and we expect BAMM and other modeling frameworks to improve in response to mathematical and computational innovations. However, we remain optimistic that that the imperfect tools currently available to comparative biologists have provided and will continue to provide important insights into the diversification of life on Earth.
subject
0BAMM
1Bayes Theorem
2Bayesian analysis
3Biodiversity
4Classification - methods
5Computer applications
6Data Interpretation, Statistical
7diversification
8Evolution
9Innovations
10Likelihood Functions
11macroevolution
12Markov analysis
13Markov chains
14Mathematical models
15Models, Biological
16Monte Carlo simulation
17Performance assessment
18Phylogenetics
19Phylogeny
20Regular
21Regular Articles
22Software
23speciation
24Statistical analysis
issn
01063-5157
11076-836X
fulltexttrue
rsrctypearticle
creationdate2017
recordtypearticle
recordideNp1ks1vFCEYxidGYz_06FFD4sXLKB_L18Vm3Vpt0lVjauKNMMB02czCCkzr_vdSp1bbxNML4fc-vDw8TfMMwdcISvIm73LnYy0_IeEPmn0EOWsFYd8fXq8ZaSmifK85yHkNIUKMosfNHhaEzDAm-83FaQbv5sslOBn0lbNH4HzlYnLFGz0AHSz4krSZdosYjEshAx9AWTkwD3rYZZ9B7MFyHIpvv-riwLG_dCn7vvYUHwNYRuuG_KR51Oshu6c39bD5dvL-fPGxPfv84XQxP2sRRby0RmNsKYdMSou4JpwxDLXkyFKheX0b7bS0FncGSsihpFJiq2FvqhcGM0oOm7eT7nbsNs4aF0rSg9omv9Fpp6L26u5J8Ct1ES8V5RIiIqrAp0kgbl3QPrk7vTa4oqyz41Zd9aoaqjgy2LJezBizhBIsGNW6owJJ3ZGOuCr46maiFH-MLhe18dm4YdDBxTErJATCjFAsK_ryHrqOY6o2V0oyBOt9FFWqnSiTYs7J9bcTIqiuM6GmTKgpE5V_8a8lt_SfEFSA3BM0vvz-vOqQH_4r-3zqWucS019VNoNCUkh-AVJCz0E
startdate20170701
enddate20170701
creator
0Rabosky, Daniel L
1Mitchell, Jonathan S
2Chang, Jonathan
general
0Oxford University Press
1Oxford University Press (OUP)
scope
0CGR
1CUY
2CVF
3ECM
4EIF
5NPM
6AAYXX
7CITATION
8K9.
97X8
10BOBZL
11CLFQK
125PM
sort
creationdate20170701
titleIs BAMM Flawed? Theoretical and Practical Concerns in the Analysis of Multi-Rate Diversification Models
authorRabosky, Daniel L ; Mitchell, Jonathan S ; Chang, Jonathan
facets
frbrtype5
frbrgroupidcdi_FETCH-LOGICAL-1517t-ca22d570699d17a376620a971d58a71075ba9dd2bc0907095992da0fc109c2653
rsrctypearticles
prefilterarticles
languageeng
creationdate2017
topic
0BAMM
1Bayes Theorem
2Bayesian analysis
3Biodiversity
4Classification - methods
5Computer applications
6Data Interpretation, Statistical
7diversification
8Evolution
9Innovations
10Likelihood Functions
11macroevolution
12Markov analysis
13Markov chains
14Mathematical models
15Models, Biological
16Monte Carlo simulation
17Performance assessment
18Phylogenetics
19Phylogeny
20Regular
21Regular Articles
22Software
23speciation
24Statistical analysis
toplevel
0peer_reviewed
1online_resources
creatorcontrib
0Rabosky, Daniel L
1Mitchell, Jonathan S
2Chang, Jonathan
collection
0Medline
1MEDLINE
2MEDLINE (Ovid)
3MEDLINE
4MEDLINE
5PubMed
6CrossRef
7ProQuest Health & Medical Complete (Alumni)
8MEDLINE - Academic
9OpenAIRE (Open Access)
10OpenAIRE
11PubMed Central (Full Participant titles)
jtitleSystematic Biology
delivery
delcategoryRemote Search Resource
fulltextfulltext
addata
au
0Rabosky, Daniel L
1Mitchell, Jonathan S
2Chang, Jonathan
formatjournal
genrearticle
ristypeJOUR
atitleIs BAMM Flawed? Theoretical and Practical Concerns in the Analysis of Multi-Rate Diversification Models
jtitleSystematic Biology
addtitleSyst Biol
date2017-07-01
risdate2017
volume66
issue4
spage477
epage498
pages477-498
issn1063-5157
eissn1076-836X
notesAssociate Editor: Thomas Near
abstractBayesian analysis of macroevolutionary mixtures (BAMM) is a statistical framework that uses reversible jump Markov chain Monte Carlo to infer complex macroevolutionary dynamics of diversification and phenotypic evolution on phylogenetic trees. A recent article by Moore et al. (MEA) reported a number of theoretical and practical concerns with BAMM. Major claims from MEA are that (i) BAMM's likelihood function is incorrect, because it does not account for unobserved rate shifts; (ii) the posterior distribution on the number of rate shifts is overly sensitive to the prior; and (iii) diversification rate estimates from BAMM are unreliable. Here, we show that these and other conclusions from MEA are generally incorrect or unjustified. We first demonstrate that MEA's numerical assessment of the BAMM likelihood is compromised by their use of an invalid likelihood function. We then show that "unobserved rate shifts" appear to be irrelevant for biologically plausible parameterizations of the diversification process. We find that the purportedly extreme prior sensitivity reported by MEA cannot be replicated with standard usage of BAMM v2.5, or with any other version when conventional Bayesian model selection is performed. Finally, we demonstrate that BAMM performs very well at estimating diversification rate variation across the ~20% of simulated trees in MEA's data set for which it is theoretically possible to infer rate shifts with confidence. Due to ascertainment bias, the remaining 80% of their purportedly variable-rate phylogenies are statistically indistinguishable from those produced by a constant-rate birth–death process and were thus poorly suited for the summary statistics used in their performance assessment. We demonstrate that inferences about diversification rates have been accurate and consistent across all major previous releases of the BAMM software. We recognize an acute need to address the theoretical foundations of rate-shift models for phylogenetic trees, and we expect BAMM and other modeling frameworks to improve in response to mathematical and computational innovations. However, we remain optimistic that that the imperfect tools currently available to comparative biologists have provided and will continue to provide important insights into the diversification of life on Earth.
copEngland
pubOxford University Press
pmid28334223
doi10.1093/sysbio/syx037
oafree_for_read