Bayesian Analysis Using a Simple Likelihood Model Outperforms Parsimony for Estimation of Phylogeny from Discrete Morphological Data
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{"title"=>"Bayesian Analysis Using a Simple Likelihood Model Outperforms Parsimony for Estimation of Phylogeny from Discrete Morphological Data", "type"=>"journal", "authors"=>[{"first_name"=>"April M.", "last_name"=>"Wright", "scopus_author_id"=>"7403738425"}, {"first_name"=>"David M.", "last_name"=>"Hillis", "scopus_author_id"=>"7005224338"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"isbn"=>"1932-6203", "scopus"=>"2-s2.0-84937538097", "pui"=>"608759004", "doi"=>"10.1371/journal.pone.0109210", "sgr"=>"84937538097", "pmid"=>"25279853", "issn"=>"19326203"}, "id"=>"e1167adb-74ce-3bd9-99d5-d810828b146f", "abstract"=>"Despite the introduction of likelihood-based methods for estimating phylogenetic trees from phenotypic data, parsimony remains the most widely-used optimality criterion for building trees from discrete morphological data. However, it has been known for decades that there are regions of solution space in which parsimony is a poor estimator of tree topology. Numerous software implementations of likelihood-based models for the estimation of phylogeny from discrete morphological data exist, especially for the Mk model of discrete character evolution. Here we explore the efficacy of Bayesian estimation of phylogeny, using the Mk model, under conditions that are commonly encountered in paleontological studies. Using simulated data, we describe the relative performances of parsimony and the Mk model under a range of realistic conditions that include common scenarios of missing data and rate heterogeneity.", "link"=>"http://www.mendeley.com/research/bayesian-analysis-using-simple-likelihood-model-outperforms-parsimony-estimation-phylogeny-discrete", "reader_count"=>203, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>6, "Researcher"=>44, "Student > Doctoral Student"=>22, "Student > Ph. D. Student"=>61, "Student > Postgraduate"=>6, "Student > Master"=>29, "Other"=>4, "Student > Bachelor"=>21, "Lecturer"=>3, "Professor"=>7}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>6, "Researcher"=>44, "Student > Doctoral Student"=>22, "Student > Ph. D. Student"=>61, "Student > Postgraduate"=>6, "Student > Master"=>29, "Other"=>4, "Student > Bachelor"=>21, "Lecturer"=>3, "Professor"=>7}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Environmental Science"=>4, "Biochemistry, Genetics and Molecular Biology"=>9, "Agricultural and Biological Sciences"=>159, "Social Sciences"=>2, "Earth and Planetary Sciences"=>25, "Linguistics"=>2}, "reader_count_by_subdiscipline"=>{"Social Sciences"=>{"Social Sciences"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>25}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>159}, "Linguistics"=>{"Linguistics"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>9}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>4}}, "reader_count_by_country"=>{"New Zealand"=>1, "Canada"=>1, "Colombia"=>2, "Sweden"=>3, "United States"=>7, "Brazil"=>13, "United Kingdom"=>2, "Mexico"=>2, "France"=>1, "Germany"=>3}, "group_count"=>2}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1704760"], "description"=>"<p>Columns represent characters. In the taxon-names column, an asterisk represents fossil taxa. Characters with the slowest rate of change are represented in light grey; intermediate-rate characters are represented in medium grey; characters with highest rate of change are represented in dark grey. In the top matrix, all characters are present for all taxa. The bottom matrices illustrate the missing data conditions that we simulated in this paper.</p>", "links"=>[], "tags"=>["phylogeny", "parsimony", "Numerous software implementations", "Discrete Morphological Data", "Simple Likelihood Model Outperforms Parsimony", "bayesian", "Mk model", "data", "estimation"], "article_id"=>1193601, "categories"=>["Biological Sciences"], "users"=>["April M. Wright", "David M. Hillis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0109210.g002", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_schematic_representing_different_missing_data_distributions_/1193601", "title"=>"A schematic representing different missing data distributions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-10-03 02:59:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1704779"], "description"=>"<p>Comparison of 350- and 1000-character data sets.</p>", "links"=>[], "tags"=>["phylogeny", "parsimony", "Numerous software implementations", "Discrete Morphological Data", "Simple Likelihood Model Outperforms Parsimony", "bayesian", "Mk model", "data", "estimation"], "article_id"=>1193620, "categories"=>["Biological Sciences"], "users"=>["April M. Wright", "David M. Hillis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0109210.g006", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_350_and_1000_character_data_sets_/1193620", "title"=>"Comparison of 350- and 1000-character data sets.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-10-03 02:59:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1704776"], "description"=>"<p>This figure compares the effect of deleting one-third of the characters from three different rate classes. (A) Comparisons of Bayesian-Mk analyses. (B) Comparisons of parsimony analyses.</p>", "links"=>[], "tags"=>["phylogeny", "parsimony", "Numerous software implementations", "Discrete Morphological Data", "Simple Likelihood Model Outperforms Parsimony", "bayesian", "Mk model", "data", "estimation"], "article_id"=>1193617, "categories"=>["Biological Sciences"], "users"=>["April M. Wright", "David M. Hillis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0109210.g005", "stats"=>{"downloads"=>2, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_effects_of_missing_data_vary_with_the_rate_of_character_evolution_/1193617", "title"=>"The effects of missing data vary with the rate of character evolution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-10-03 02:59:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1704768"], "description"=>"<p>Bayesian-Mk outperforms parsimony most strongly when the rate of character evolution (and hence homoplasy) is high.</p>", "links"=>[], "tags"=>["phylogeny", "parsimony", "Numerous software implementations", "Discrete Morphological Data", "Simple Likelihood Model Outperforms Parsimony", "bayesian", "Mk model", "data", "estimation"], "article_id"=>1193609, "categories"=>["Biological Sciences"], "users"=>["April M. Wright", "David M. Hillis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0109210.g003", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_from_simulations_with_a_single_rate_of_character_evolution_/1193609", "title"=>"Results from simulations with a single rate of character evolution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-10-03 02:59:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1704782", "https://ndownloader.figshare.com/files/1704783"], "description"=>"<div><p>Despite the introduction of likelihood-based methods for estimating phylogenetic trees from phenotypic data, parsimony remains the most widely-used optimality criterion for building trees from discrete morphological data. However, it has been known for decades that there are regions of solution space in which parsimony is a poor estimator of tree topology. Numerous software implementations of likelihood-based models for the estimation of phylogeny from discrete morphological data exist, especially for the Mk model of discrete character evolution. Here we explore the efficacy of Bayesian estimation of phylogeny, using the Mk model, under conditions that are commonly encountered in paleontological studies. Using simulated data, we describe the relative performances of parsimony and the Mk model under a range of realistic conditions that include common scenarios of missing data and rate heterogeneity.</p></div>", "links"=>[], "tags"=>["phylogeny", "parsimony", "Numerous software implementations", "Discrete Morphological Data", "Simple Likelihood Model Outperforms Parsimony", "bayesian", "Mk model", "data", "estimation"], "article_id"=>1193623, "categories"=>["Biological Sciences"], "users"=>["April M. Wright", "David M. Hillis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0109210.s001", "https://dx.doi.org/10.1371/journal.pone.0109210.s002"], "stats"=>{"downloads"=>3, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Bayesian_Analysis_Using_a_Simple_Likelihood_Model_Outperforms_Parsimony_for_Estimation_of_Phylogeny_from_Discrete_Morphological_Data_/1193623", "title"=>"Bayesian Analysis Using a Simple Likelihood Model Outperforms Parsimony for Estimation of Phylogeny from Discrete Morphological Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-10-03 02:59:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1704771"], "description"=>"<p>Note that, unlike <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109210#pone-0109210-g003\" target=\"_blank\">Figure 3</a>, the X-axis is the average rate of change across all characters in the data set, as opposed to one single rate applied uniformly to all characters.</p>", "links"=>[], "tags"=>["phylogeny", "parsimony", "Numerous software implementations", "Discrete Morphological Data", "Simple Likelihood Model Outperforms Parsimony", "bayesian", "Mk model", "data", "estimation"], "article_id"=>1193612, "categories"=>["Biological Sciences"], "users"=>["April M. Wright", "David M. Hillis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0109210.g004", "stats"=>{"downloads"=>4, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_In_data_sets_with_character_rate_heterogeneity_and_with_no_missing_data_Bayesian_Mk_results_in_lower_error_compared_to_parsimony_analyses_/1193612", "title"=>"In data sets with character rate heterogeneity and with no missing data, Bayesian-Mk results in lower error compared to parsimony analyses.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-10-03 02:59:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/1704757"], "description"=>"<p>This tree was obtained from a combined molecular–phenotypic data set analyzed by Pyron <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109210#pone.0109210-Pyron1\" target=\"_blank\">[27]</a>.</p>", "links"=>[], "tags"=>["phylogeny", "parsimony", "Numerous software implementations", "Discrete Morphological Data", "Simple Likelihood Model Outperforms Parsimony", "bayesian", "Mk model", "data", "estimation"], "article_id"=>1193598, "categories"=>["Biological Sciences"], "users"=>["April M. Wright", "David M. Hillis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0109210.g001", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Tree_used_for_simulations_/1193598", "title"=>"Tree used for simulations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-10-03 02:59:31"}

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Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Computer and information sciences/Data management", "average_usage"=>[365, 545]}, {"subject_area"=>"/Earth sciences", "average_usage"=>[318]}, {"subject_area"=>"/Earth sciences/Paleontology", "average_usage"=>[557, 890]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[271]}]}
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