• Help

•

Quantifying and Comparing Phylogenetic Evolutionary Rates for Shape and Other High-Dimensional Phenotypic Data

Many questions in evolutionary biology require the quantification and comparison of rates of phenotypic evolution. Recently, phylogenetic comparative methods have been developed for comparing evolutionary rates on a phylogeny for single, univariate traits (σ²), and evolutionary rate matrices (R) for... Full description

 Journal Title: Systematic biology 2014, Vol.63 (2), p.166-177 Main Author: Adams, Dean C Format: 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/24335426 Zum Text:
Staff View
 recordid: cdi_proquest_miscellaneous_1500689752 title: Quantifying and Comparing Phylogenetic Evolutionary Rates for Shape and Other High-Dimensional Phenotypic Data format: Article creator: Adams, Dean C subjects: Animals Biological evolution Biological taxonomies Classification - methods Comparative analysis Covariance matrices Evolution Evolutionary biology Genotype & phenotype Geometric shapes Phenotype Phenotypic traits Phylogenetics Phylogeny Reptiles & amphibians Salamanders Taxa Time Urodela - anatomy & histology Urodela - classification ispartof: Systematic biology, 2014, Vol.63 (2), p.166-177 description: Many questions in evolutionary biology require the quantification and comparison of rates of phenotypic evolution. Recently, phylogenetic comparative methods have been developed for comparing evolutionary rates on a phylogeny for single, univariate traits (σ²), and evolutionary rate matrices (R) for sets of traits treated simultaneously. However, high-dimensional traits like shape remain under-examined with this framework, because methods suited for such data have not been fully developed. In this article, I describe a method to quantify phylogenetic evolutionary rates for high-dimensional multivariate data $\left( {\sigma _{mult}^2} \right)$, found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices (R-mode and Q-mode methods). I then use simulations to evaluate the statistical performance of hypothesis-testing procedures that compare $\sigma _{mult}^1$ for two or more groups of species on a phylogeny. Under both isotropic and non-isotropic conditions, and for differing numbers of trait dimensions, the proposed method displays appropriate Type I error and high statistical power for detecting known differences in $\sigma _{mult}^1$ among groups. In contrast, the Type I error rate of likelihood tests based on the evolutionary rate matrix (R) increases as the number of trait dimensions (p) increases, and becomes unacceptably large when only a few trait dimensions are considered. Further, likelihood tests based on R cannot be computed when the number of trait dimensions equals or exceeds the number of taxa in the phylogeny (i.e., when p> N). These results demonstrate that tests based on $\sigma _{mult}^1$ provide a useful means of comparing evolutionary rates for high-dimensional data that are otherwise not analytically accessible to methods based on the evolutionary rate matrix. This advance thus expands the phylogenetic comparative toolkit for high-dimensional phenotypic traits like shape. Finally, I illustrate the utility of the new approach by evaluating rates of head shape evolution in a lineage of Plethodon salamanders. language: eng source: Alma/SFX Local Collection identifier: ISSN: 1063-5157 fulltext: fulltext issn: 1063-5157 1076-836X url: Link

@attributes
 NO 1 SEARCH_ENGINE primo_central_multiple_fe SEARCH_ENGINE_TYPE Primo Central Search Engine RANK 2.6956255 LOCAL false
PrimoNMBib
record
control
 sourceid jstor_opena recordid TN_cdi_proquest_miscellaneous_1500689752 sourceformat XML sourcesystem PC jstor_id 43700566 oup_id 10.1093/sysbio/syt105 sourcerecordid 43700566 originalsourceid FETCH-LOGICAL-1491t-ae99515d34763f5f2b1cf5624498a8a87f4bf8980bf427de546486a29a21cedc3 addsrcrecordid eNqFkc2L1DAYh4so7rp69KgUvHip5rvNUWZXV1lYP8FbeJsmMxk6TU1Sof-96Xacw4JIDkngycPvza8onmP0BiNJ38Y5ts7nLWHEHxTnGNWiaqj4-XA5C1pxzOuz4kmMe4QwFhw_Ls4Io5QzIs6L4csEQ3J2dsO2hKErN_4wQlhun3dz77dmMMnp8uq376fk_ABhLr9CMrG0PpTfdjCau3e3aWdCee22u-rSHcwQF7bPEjP4NI9ZcQkJnhaPLPTRPDvuF8WP91ffN9fVze2Hj5t3NxVmEqcKjJQ5d0dZLajllrRYWy4IY7KBvGrLWtvIBrWWkboznAnWCCASCNam0_Si-LR6_WgGcMGoMbhDzq48ONXlmVSX42iXjGoZWMtZ1xBTaywJIloDJbWlCKTANster7Ix-F-TiUkdXNSm72EwfooKc4REI2tOMvrqHrr3U8gfcUflrJQwmalqpXTwMQZjT-kwUkuram1Vra1m_uXROrUH053ovzVmgN4T5slgqSsFcP0_tce5_DT-N8GLFd3H5MMJZrRGiAtB_wAo7soZ sourcetype Open Access Repository isCDI true recordtype article pqid 1504273249
display
typearticle
titleQuantifying and Comparing Phylogenetic Evolutionary Rates for Shape and Other High-Dimensional Phenotypic Data
sourceAlma/SFX Local Collection
descriptionMany questions in evolutionary biology require the quantification and comparison of rates of phenotypic evolution. Recently, phylogenetic comparative methods have been developed for comparing evolutionary rates on a phylogeny for single, univariate traits (σ²), and evolutionary rate matrices (R) for sets of traits treated simultaneously. However, high-dimensional traits like shape remain under-examined with this framework, because methods suited for such data have not been fully developed. In this article, I describe a method to quantify phylogenetic evolutionary rates for high-dimensional multivariate data $\left( {\sigma _{mult}^2} \right)$, found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices (R-mode and Q-mode methods). I then use simulations to evaluate the statistical performance of hypothesis-testing procedures that compare $\sigma _{mult}^1$ for two or more groups of species on a phylogeny. Under both isotropic and non-isotropic conditions, and for differing numbers of trait dimensions, the proposed method displays appropriate Type I error and high statistical power for detecting known differences in $\sigma _{mult}^1$ among groups. In contrast, the Type I error rate of likelihood tests based on the evolutionary rate matrix (R) increases as the number of trait dimensions (p) increases, and becomes unacceptably large when only a few trait dimensions are considered. Further, likelihood tests based on R cannot be computed when the number of trait dimensions equals or exceeds the number of taxa in the phylogeny (i.e., when p> N). These results demonstrate that tests based on $\sigma _{mult}^1$ provide a useful means of comparing evolutionary rates for high-dimensional data that are otherwise not analytically accessible to methods based on the evolutionary rate matrix. This advance thus expands the phylogenetic comparative toolkit for high-dimensional phenotypic traits like shape. Finally, I illustrate the utility of the new approach by evaluating rates of head shape evolution in a lineage of Plethodon salamanders.
identifier
 0 ISSN: 1063-5157 1 EISSN: 1076-836X 2 DOI: 10.1093/sysbio/syt105 3 PMID: 24335426
languageeng
publisherEngland: Oxford University Press
subjectAnimals ; Biological evolution ; Biological taxonomies ; Classification - methods ; Comparative analysis ; Covariance matrices ; Evolution ; Evolutionary biology ; Genotype & phenotype ; Geometric shapes ; Phenotype ; Phenotypic traits ; Phylogenetics ; Phylogeny ; Reptiles & amphibians ; Salamanders ; Taxa ; Time ; Urodela - anatomy & histology ; Urodela - classification
ispartofSystematic biology, 2014, Vol.63 (2), p.166-177
rights
lds50peer_reviewed
citedbyFETCH-LOGICAL-1491t-ae99515d34763f5f2b1cf5624498a8a87f4bf8980bf427de546486a29a21cedc3
citesFETCH-LOGICAL-1491t-ae99515d34763f5f2b1cf5624498a8a87f4bf8980bf427de546486a29a21cedc3
 openurl $$Topenurl_article openurlfulltext$$Topenurlfull_article thumbnail $$Usyndetics_thumb_exl backlink$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24335426D View this record in MEDLINE/PubMed
search
title
 0 Quantifying and Comparing Phylogenetic Evolutionary Rates for Shape and Other High-Dimensional Phenotypic Data 1 Systematic biology
descriptionMany questions in evolutionary biology require the quantification and comparison of rates of phenotypic evolution. Recently, phylogenetic comparative methods have been developed for comparing evolutionary rates on a phylogeny for single, univariate traits (σ²), and evolutionary rate matrices (R) for sets of traits treated simultaneously. However, high-dimensional traits like shape remain under-examined with this framework, because methods suited for such data have not been fully developed. In this article, I describe a method to quantify phylogenetic evolutionary rates for high-dimensional multivariate data $\left( {\sigma _{mult}^2} \right)$, found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices (R-mode and Q-mode methods). I then use simulations to evaluate the statistical performance of hypothesis-testing procedures that compare $\sigma _{mult}^1$ for two or more groups of species on a phylogeny. Under both isotropic and non-isotropic conditions, and for differing numbers of trait dimensions, the proposed method displays appropriate Type I error and high statistical power for detecting known differences in $\sigma _{mult}^1$ among groups. In contrast, the Type I error rate of likelihood tests based on the evolutionary rate matrix (R) increases as the number of trait dimensions (p) increases, and becomes unacceptably large when only a few trait dimensions are considered. Further, likelihood tests based on R cannot be computed when the number of trait dimensions equals or exceeds the number of taxa in the phylogeny (i.e., when p> N). These results demonstrate that tests based on $\sigma _{mult}^1$ provide a useful means of comparing evolutionary rates for high-dimensional data that are otherwise not analytically accessible to methods based on the evolutionary rate matrix. This advance thus expands the phylogenetic comparative toolkit for high-dimensional phenotypic traits like shape. Finally, I illustrate the utility of the new approach by evaluating rates of head shape evolution in a lineage of Plethodon salamanders.
subject
 0 Animals 1 Biological evolution 2 Biological taxonomies 3 Classification - methods 4 Comparative analysis 5 Covariance matrices 6 Evolution 7 Evolutionary biology 8 Genotype & phenotype 9 Geometric shapes 10 Phenotype 11 Phenotypic traits 12 Phylogenetics 13 Phylogeny 14 Reptiles & amphibians 15 Salamanders 16 Taxa 17 Time 18 Urodela - anatomy & histology 19 Urodela - classification
issn
 0 1063-5157 1 1076-836X
fulltexttrue
rsrctypearticle
creationdate2014
recordtypearticle
recordideNqFkc2L1DAYh4so7rp69KgUvHip5rvNUWZXV1lYP8FbeJsmMxk6TU1Sof-96Xacw4JIDkngycPvza8onmP0BiNJ38Y5ts7nLWHEHxTnGNWiaqj4-XA5C1pxzOuz4kmMe4QwFhw_Ls4Io5QzIs6L4csEQ3J2dsO2hKErN_4wQlhun3dz77dmMMnp8uq376fk_ABhLr9CMrG0PpTfdjCau3e3aWdCee22u-rSHcwQF7bPEjP4NI9ZcQkJnhaPLPTRPDvuF8WP91ffN9fVze2Hj5t3NxVmEqcKjJQ5d0dZLajllrRYWy4IY7KBvGrLWtvIBrWWkboznAnWCCASCNam0_Si-LR6_WgGcMGoMbhDzq48ONXlmVSX42iXjGoZWMtZ1xBTaywJIloDJbWlCKTANster7Ix-F-TiUkdXNSm72EwfooKc4REI2tOMvrqHrr3U8gfcUflrJQwmalqpXTwMQZjT-kwUkuram1Vra1m_uXROrUH053ovzVmgN4T5slgqSsFcP0_tce5_DT-N8GLFd3H5MMJZrRGiAtB_wAo7soZ
startdate20140301
enddate20140301
general
 0 Oxford University Press 1 Oxford University Press (OUP)
scope
 0 CGR 1 CUY 2 CVF 3 ECM 4 EIF 5 NPM 6 AAYXX 7 CITATION 8 K9. 9 7X8 10 CLFQK
sort
 creationdate 20140301 title Quantifying and Comparing Phylogenetic Evolutionary Rates for Shape and Other High-Dimensional Phenotypic Data author Adams, Dean C
facets
frbrtype5
frbrgroupidcdi_FETCH-LOGICAL-1491t-ae99515d34763f5f2b1cf5624498a8a87f4bf8980bf427de546486a29a21cedc3
rsrctypearticles
prefilterarticles
languageeng
creationdate2014
topic
 0 Animals 1 Biological evolution 2 Biological taxonomies 3 Classification - methods 4 Comparative analysis 5 Covariance matrices 6 Evolution 7 Evolutionary biology 8 Genotype & phenotype 9 Geometric shapes 10 Phenotype 11 Phenotypic traits 12 Phylogenetics 13 Phylogeny 14 Reptiles & amphibians 15 Salamanders 16 Taxa 17 Time 18 Urodela - anatomy & histology 19 Urodela - classification
toplevel
 0 peer_reviewed 1 online_resources
 au Adams, Dean C format journal genre article ristype JOUR atitle Quantifying and Comparing Phylogenetic Evolutionary Rates for Shape and Other High-Dimensional Phenotypic Data jtitle Systematic biology addtitle Syst Biol date 2014-03-01 risdate 2014 volume 63 issue 2 spage 166 epage 177 pages 166-177 issn 1063-5157 eissn 1076-836X abstract Many questions in evolutionary biology require the quantification and comparison of rates of phenotypic evolution. Recently, phylogenetic comparative methods have been developed for comparing evolutionary rates on a phylogeny for single, univariate traits (σ²), and evolutionary rate matrices (R) for sets of traits treated simultaneously. However, high-dimensional traits like shape remain under-examined with this framework, because methods suited for such data have not been fully developed. In this article, I describe a method to quantify phylogenetic evolutionary rates for high-dimensional multivariate data $\left( {\sigma _{mult}^2} \right)$, found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices (R-mode and Q-mode methods). I then use simulations to evaluate the statistical performance of hypothesis-testing procedures that compare $\sigma _{mult}^1$ for two or more groups of species on a phylogeny. Under both isotropic and non-isotropic conditions, and for differing numbers of trait dimensions, the proposed method displays appropriate Type I error and high statistical power for detecting known differences in $\sigma _{mult}^1$ among groups. In contrast, the Type I error rate of likelihood tests based on the evolutionary rate matrix (R) increases as the number of trait dimensions (p) increases, and becomes unacceptably large when only a few trait dimensions are considered. Further, likelihood tests based on R cannot be computed when the number of trait dimensions equals or exceeds the number of taxa in the phylogeny (i.e., when p> N). These results demonstrate that tests based on $\sigma _{mult}^1$ provide a useful means of comparing evolutionary rates for high-dimensional data that are otherwise not analytically accessible to methods based on the evolutionary rate matrix. This advance thus expands the phylogenetic comparative toolkit for high-dimensional phenotypic traits like shape. Finally, I illustrate the utility of the new approach by evaluating rates of head shape evolution in a lineage of Plethodon salamanders. cop England pub Oxford University Press pmid 24335426 doi 10.1093/sysbio/syt105 oa free_for_read