├── .gitignore
├── README.md
├── abstracts
├── 01-introduction-phylogenetic-comparative-method.md
├── 02-working-tree-life-comparative-studies-build-tailor-phylogenies-interspecific-datasets.md
├── 03-introduction-supertree-construction-partitioned-phylogenetic-analyses-view-toward-distinction-gene-trees-species-trees.md
├── 04-graphical-methods-visualizing-comparative-data-phylogenies.md
├── 05-primer-phylogenetic-generalised-least-squares.md
├── 06-statistical-issues-assumptions-phylogenetic-generalised-least-squares.md
├── 07-uncertainties-due-within-species-variation-comparative-studies-measurement-errors-statistical-weights.md
├── 08-introduction-phylogenetic-path-analysis.md
├── 09-phylogenetic-logistic-regression-binary-dependent-variables.md
├── 10-keeping-updated-bayesian-approaches-phylogenetic-comparative-methods-focus-markov-chain-models-discrete-character-evolution.md
├── 11-general-quantitative-genetic-methods-comparative-biology.md
├── 12-multimodel-inference-comparative-analyses.md
├── 13-simulation-phylogenetic-data.md
├── 14-use-misuse-comparative-methods-study-adaptation.md
├── 15-modelling-stabilising-selection-attraction-ornstein-uhlenbeck-models.md
├── 16-hidden-markov-models-studying-evolution-binary-morphological-characters.md
├── 17-detecting-phenotypic-selection-approximate-bayesian-computation-abc-phylogenetic-comparative-methods.md
├── 18-phylogenetic-comparative-methods-studying-clade-wide-convergence.md
├── 19-metrics-models-community-phylogenetics.md
├── 20-event-based-cophylogenetic-comparative-analysis.md
├── 21-phylogenetic-prediction-identify-evolutionary-singularities.md
├── 22-preparing-paleontological-datasets-phylogenetic-comparative-methods.md
└── README.md
├── authors.md
├── backup
├── additional_files
│ ├── ch10
│ │ ├── ch10_figures.md
│ │ ├── unnamed-chunk-1.png
│ │ ├── unnamed-chunk-10.png
│ │ ├── unnamed-chunk-11.png
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│ ├── ch11
│ │ ├── ch11_figures.md
│ │ ├── unnamed-chunk-1.png
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│ ├── ch12
│ │ ├── unnamed-chunk-2.png
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│ ├── ch13
│ │ ├── unnamed-chunk-15.png
│ │ └── unnamed-chunk-16.png
│ ├── ch17
│ │ └── image001.png
│ ├── ch2
│ │ ├── ch2_figures.md
│ │ ├── unnamed-chunk-10.png
│ │ ├── unnamed-chunk-11.png
│ │ ├── unnamed-chunk-17.png
│ │ ├── unnamed-chunk-181.png
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│ │ ├── unnamed-chunk-7.png
│ │ └── unnamed-chunk-9.png
│ ├── ch21
│ │ ├── unnamed-chunk-2.png
│ │ ├── unnamed-chunk-31.png
│ │ ├── unnamed-chunk-32.png
│ │ ├── unnamed-chunk-33.png
│ │ ├── unnamed-chunk-34.png
│ │ └── unnamed-chunk-35.png
│ ├── ch22
│ │ ├── unnamed-chunk-10.png
│ │ ├── unnamed-chunk-11.png
│ │ ├── unnamed-chunk-13.png
│ │ ├── unnamed-chunk-14.png
│ │ ├── unnamed-chunk-17.png
│ │ ├── unnamed-chunk-181.png
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│ │ ├── unnamed-chunk-221.png
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│ │ ├── unnamed-chunk-3.png
│ │ ├── unnamed-chunk-41.png
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│ │ ├── unnamed-chunk-64.png
│ │ ├── unnamed-chunk-7.png
│ │ ├── unnamed-chunk-8.png
│ │ └── unnamed-chunk-9.png
│ ├── ch4
│ │ ├── ch4_figures.md
│ │ ├── unnamed-chunk-1.png
│ │ ├── unnamed-chunk-10.png
│ │ ├── unnamed-chunk-11.png
│ │ ├── unnamed-chunk-12.png
│ │ ├── unnamed-chunk-2.png
│ │ ├── unnamed-chunk-3.png
│ │ ├── unnamed-chunk-4.png
│ │ ├── unnamed-chunk-5.png
│ │ ├── unnamed-chunk-6.png
│ │ ├── unnamed-chunk-7.png
│ │ ├── unnamed-chunk-8.png
│ │ └── unnamed-chunk-9.png
│ ├── ch5
│ │ ├── ch5_figures.md
│ │ ├── unnamed-chunk-1.png
│ │ ├── unnamed-chunk-2.png
│ │ ├── unnamed-chunk-3.png
│ │ ├── unnamed-chunk-4.png
│ │ ├── unnamed-chunk-5.png
│ │ └── unnamed-chunk-6.png
│ ├── ch6
│ │ ├── ch6_figures.md
│ │ ├── unnamed-chunk-1.png
│ │ ├── unnamed-chunk-31.png
│ │ ├── unnamed-chunk-32.png
│ │ ├── unnamed-chunk-33.png
│ │ ├── unnamed-chunk-34.png
│ │ ├── unnamed-chunk-35.png
│ │ ├── unnamed-chunk-36.png
│ │ ├── unnamed-chunk-61.png
│ │ ├── unnamed-chunk-62.png
│ │ ├── unnamed-chunk-63.png
│ │ └── unnamed-chunk-64.png
│ ├── ch7
│ │ ├── ch7_figures.md
│ │ ├── unnamed-chunk-1.png
│ │ ├── unnamed-chunk-2.png
│ │ ├── unnamed-chunk-3.png
│ │ ├── unnamed-chunk-4.png
│ │ └── unnamed-chunk-6.png
│ └── ch8
│ │ ├── ch8_figures.md
│ │ ├── unnamed-chunk-2.png
│ │ ├── unnamed-chunk-36.png
│ │ ├── unnamed-chunk-4.png
│ │ └── unnamed-chunk-5.png
├── book-sections.md
├── book
│ └── CHAPTERS
│ │ ├── 1-introduction-phylogenetic-comparative-method.md
│ │ ├── 10-keeping-updated-bayesian-approaches-phylogenetic-comparative-methods-focus-markov-chain-models-discrete-character-evolution.md
│ │ ├── 11-general-quantitative-genetic-methods-comparative-biology.md
│ │ ├── 12-multimodel-inference-comparative-analyses.md
│ │ ├── 13-simulation-phylogenetic-data.md
│ │ ├── 14-use-misuse-comparative-methods-study-adaptation.md
│ │ ├── 15-modelling-stabilising-selection-attraction-ornstein-uhlenbeck-models.md
│ │ ├── 16-hidden-markov-models-studying-evolution-binary-morphological-characters.md
│ │ ├── 17-detecting-phenotypic-selection-approximate-bayesian-computation-abc-phylogenetic-comparative-methods.md
│ │ ├── 18-phylogenetic-comparative-methods-studying-clade-wide-convergence.md
│ │ ├── 19-metrics-models-community-phylogenetics.md
│ │ ├── 2-working-tree-life-comparative-studies-build-tailor-phylogenies-interspecific-datasets.md
│ │ ├── 20-event-based-cophylogenetic-comparative-analysis.md
│ │ ├── 21-phylogenetic-prediction-identify-evolutionary-singularities.md
│ │ ├── 22-preparing-paleontological-datasets-phylogenetic-comparative-methods.md
│ │ ├── 3-introduction-supertree-construction-partitioned-phylogenetic-analyses-view-toward-distinction-gene-trees-species-trees.md
│ │ ├── 4-graphical-methods-visualizing-comparative-data-phylogenies.md
│ │ ├── 5-primer-phylogenetic-generalised-least-squares.md
│ │ ├── 6-statistical-issues-assumptions-phylogenetic-generalised-least-squares.md
│ │ ├── 7-uncertainties-due-within-species-variation-comparative-studies-measurement-errors-statistical-weights.md
│ │ ├── 8-introduction-phylogenetic-path-analysis.md
│ │ └── 9-phylogenetic-logistic-regression-binary-dependent-variables.md
├── data_files
│ ├── ch10
│ │ ├── Primates.trees
│ │ ├── Primates.txt
│ │ └── ch10_data.md
│ ├── ch11
│ │ ├── ch11_data.md
│ │ ├── data_effect.txt
│ │ ├── data_pois.txt
│ │ ├── data_pois_missing.txt
│ │ ├── data_repeat.txt
│ │ ├── data_simple.txt
│ │ └── phylo.nex
│ ├── ch12
│ │ ├── 10kTrees_Primates.nex
│ │ ├── consensusTre_Primates.nex
│ │ ├── primate_data.txt
│ │ ├── primate_spec.txt
│ │ └── primate_tree.nex
│ ├── ch17
│ │ └── ABC_PCM.c
│ ├── ch19
│ │ ├── figures.R
│ │ ├── functions.R
│ │ ├── metrics.R
│ │ ├── pglmm.R
│ │ └── tables.pdf
│ ├── ch2
│ │ ├── Bird_tree5.nex
│ │ ├── Bird_tree7.tre
│ │ ├── bird_trees.tre
│ │ ├── ch2_data.md
│ │ ├── primate_spec.txt
│ │ └── primate_tree.phy
│ ├── ch21
│ │ ├── BayesModelS_v22.R
│ │ ├── e.IMI.TreeBlock_10kTrees_Primates_Version3.nex.txt
│ │ └── e.dataIMI_corrected.csv
│ ├── ch4
│ │ ├── Centrarchidae.tre
│ │ ├── anole.data.csv
│ │ ├── ch4_data.md
│ │ ├── elopomorph.csv
│ │ └── elopomorph.tre
│ ├── ch5
│ │ ├── ch5_data.md
│ │ └── vcv2phylo.R
│ ├── ch6
│ │ ├── ch6_data.md
│ │ ├── covariates.txt
│ │ ├── fict_phylo.nex
│ │ └── pgls_check_fncs.r
│ ├── ch7
│ │ ├── GLSME.R
│ │ ├── ch7_data.md
│ │ ├── primate_ind.txt
│ │ ├── primate_spec.txt
│ │ └── primate_tree.phy
│ └── ch8
│ │ ├── ch8_data.md
│ │ ├── rhino.csv
│ │ ├── rhino.tree
│ │ └── storks.csv
├── modern-phylogenetic-comparative-methods-application-evolutionary-biology-concepts-practice.md
├── part-ii-handling-phylogenies-different-statistical-designs.md
├── part-iii-specific-models-studying-evolutionary-mechanisms.md
└── part-introduction.md
└── online_practical_material
├── 02-chapter.md
├── README.md
├── additional_files
├── ch10
│ ├── ch10_figures.md
│ ├── unnamed-chunk-1.png
│ ├── unnamed-chunk-10.png
│ ├── unnamed-chunk-11.png
│ ├── unnamed-chunk-12.png
│ ├── unnamed-chunk-2.png
│ ├── unnamed-chunk-3.png
│ ├── unnamed-chunk-4.png
│ ├── unnamed-chunk-5.png
│ ├── unnamed-chunk-6.png
│ ├── unnamed-chunk-7.png
│ ├── unnamed-chunk-8.png
│ └── unnamed-chunk-9.png
├── ch11
│ ├── ch11_figures.md
│ ├── unnamed-chunk-1.png
│ ├── unnamed-chunk-2.png
│ └── unnamed-chunk-3.png
├── ch12
│ ├── unnamed-chunk-2.png
│ ├── unnamed-chunk-4.png
│ ├── unnamed-chunk-7.png
│ └── unnamed-chunk-9.png
├── ch13
│ ├── unnamed-chunk-15.png
│ └── unnamed-chunk-16.png
├── ch17
│ └── image001.png
├── ch2
│ ├── ch2_figures.md
│ ├── unnamed-chunk-10.png
│ ├── unnamed-chunk-11.png
│ ├── unnamed-chunk-17.png
│ ├── unnamed-chunk-181.png
│ ├── unnamed-chunk-182.png
│ ├── unnamed-chunk-20.png
│ ├── unnamed-chunk-221.png
│ ├── unnamed-chunk-222.png
│ ├── unnamed-chunk-223.png
│ ├── unnamed-chunk-3.png
│ ├── unnamed-chunk-41.png
│ ├── unnamed-chunk-42.png
│ ├── unnamed-chunk-61.png
│ ├── unnamed-chunk-62.png
│ ├── unnamed-chunk-63.png
│ ├── unnamed-chunk-64.png
│ ├── unnamed-chunk-7.png
│ └── unnamed-chunk-9.png
├── ch21
│ ├── unnamed-chunk-2.png
│ ├── unnamed-chunk-31.png
│ ├── unnamed-chunk-32.png
│ ├── unnamed-chunk-33.png
│ ├── unnamed-chunk-34.png
│ └── unnamed-chunk-35.png
├── ch22
│ ├── unnamed-chunk-10.png
│ ├── unnamed-chunk-11.png
│ ├── unnamed-chunk-13.png
│ ├── unnamed-chunk-14.png
│ ├── unnamed-chunk-17.png
│ ├── unnamed-chunk-181.png
│ ├── unnamed-chunk-182.png
│ ├── unnamed-chunk-20.png
│ ├── unnamed-chunk-221.png
│ ├── unnamed-chunk-222.png
│ ├── unnamed-chunk-223.png
│ ├── unnamed-chunk-3.png
│ ├── unnamed-chunk-41.png
│ ├── unnamed-chunk-42.png
│ ├── unnamed-chunk-6.png
│ ├── unnamed-chunk-61.png
│ ├── unnamed-chunk-62.png
│ ├── unnamed-chunk-63.png
│ ├── unnamed-chunk-64.png
│ ├── unnamed-chunk-7.png
│ ├── unnamed-chunk-8.png
│ └── unnamed-chunk-9.png
├── ch4
│ ├── ch4_figures.md
│ ├── unnamed-chunk-1.png
│ ├── unnamed-chunk-10.png
│ ├── unnamed-chunk-11.png
│ ├── unnamed-chunk-12.png
│ ├── unnamed-chunk-2.png
│ ├── unnamed-chunk-3.png
│ ├── unnamed-chunk-4.png
│ ├── unnamed-chunk-5.png
│ ├── unnamed-chunk-6.png
│ ├── unnamed-chunk-7.png
│ ├── unnamed-chunk-8.png
│ └── unnamed-chunk-9.png
├── ch5
│ ├── ch5_figures.md
│ ├── unnamed-chunk-1.png
│ ├── unnamed-chunk-2.png
│ ├── unnamed-chunk-3.png
│ ├── unnamed-chunk-4.png
│ ├── unnamed-chunk-5.png
│ └── unnamed-chunk-6.png
├── ch6
│ ├── ch6_figures.md
│ ├── unnamed-chunk-1.png
│ ├── unnamed-chunk-31.png
│ ├── unnamed-chunk-32.png
│ ├── unnamed-chunk-33.png
│ ├── unnamed-chunk-34.png
│ ├── unnamed-chunk-35.png
│ ├── unnamed-chunk-36.png
│ ├── unnamed-chunk-61.png
│ ├── unnamed-chunk-62.png
│ ├── unnamed-chunk-63.png
│ └── unnamed-chunk-64.png
├── ch7
│ ├── ch7_figures.md
│ ├── unnamed-chunk-1.png
│ ├── unnamed-chunk-2.png
│ ├── unnamed-chunk-3.png
│ ├── unnamed-chunk-4.png
│ └── unnamed-chunk-6.png
└── ch8
│ ├── ch8_figures.md
│ ├── unnamed-chunk-2.png
│ ├── unnamed-chunk-36.png
│ ├── unnamed-chunk-4.png
│ └── unnamed-chunk-5.png
├── data_files
├── ch10
│ ├── Primates.trees
│ ├── Primates.txt
│ └── ch10_data.md
├── ch11
│ ├── ch11_data.md
│ ├── data_effect.txt
│ ├── data_pois.txt
│ ├── data_pois_missing.txt
│ ├── data_repeat.txt
│ ├── data_simple.txt
│ └── phylo.nex
├── ch12
│ ├── 10kTrees_Primates.nex
│ ├── consensusTre_Primates.nex
│ ├── primate_data.txt
│ ├── primate_spec.txt
│ └── primate_tree.nex
├── ch17
│ └── ABC_PCM.c
├── ch19
│ ├── figures.R
│ ├── functions.R
│ ├── metrics.R
│ ├── pglmm.R
│ └── tables.pdf
├── ch2
│ ├── Bird_tree5.nex
│ ├── Bird_tree7.tre
│ ├── bird_trees.tre
│ ├── ch2_data.md
│ ├── primate_spec.txt
│ └── primate_tree.phy
├── ch21
│ ├── BayesModelS_v22.R
│ ├── e.IMI.TreeBlock_10kTrees_Primates_Version3.nex.txt
│ └── e.dataIMI_corrected.csv
├── ch4
│ ├── Centrarchidae.tre
│ ├── anole.data.csv
│ ├── ch4_data.md
│ ├── elopomorph.csv
│ └── elopomorph.tre
├── ch5
│ ├── ch5_data.md
│ └── vcv2phylo.R
├── ch6
│ ├── ch6_data.md
│ ├── covariates.txt
│ ├── fict_phylo.nex
│ └── pgls_check_fncs.r
├── ch7
│ ├── GLSME.R
│ ├── ch7_data.md
│ ├── primate_ind.txt
│ ├── primate_spec.txt
│ └── primate_tree.phy
└── ch8
│ ├── ch8_data.md
│ ├── rhino.csv
│ ├── rhino.tree
│ └── storks.csv
├── exercises_and_tutorials
├── chapter-10-keeping-updated-bayesian-approaches-phylogenetic-comparative-methods-focus-markov-chain-models-discrete-character-evolution.md
├── chapter-11-1-simple-model-mcmcglmm.md
├── chapter-11-2-multiple-measurements-model-mcmcglmm.md
├── chapter-11-3-example-meta-analysis-fishers-transformation-r-zr.md
├── chapter-11-4-example-non-gaussian-trait-using-count-data.md
├── chapter-11-bibliography.md
├── chapter-11-example-mar-comparative-data.md
├── chapter-12-1-evolutionary-models-different-combinations-predictors.md
├── chapter-12-2-dealing-phylogenetic-uncertainty-inference-across-models-considering-different-phylogenetic-hypotheses.md
├── chapter-12-3-playing-statistical-weights-adjusting-omega-parameter.md
├── chapter-12-4-multimodel-inference-exploring-multidimensional-parameter-space-simultaneously-varying-lambda-omega.md
├── chapter-13-1-trees.md
├── chapter-13-2-traits.md
├── chapter-13-3-trees-traits.md
├── chapter-17-1-brief-description-program-code.md
├── chapter-19-1-calculating-community-phylogenetic-metrics-opm.md
├── chapter-2-1-exercises-building-manipulating-phylogenetic-trees.md
├── chapter-21-1-exercises-analyses-displaying-results.md
├── chapter-22-1-example-time-scaling-using-r-package-paleotree.md
├── chapter-4-1-codes-used-produce-twelve-figures-chapter.md
├── chapter-6-1exercises-testing-assumptions-statistical-issues-framework-phylogenetic-generalized-least-squares.md
├── chapter-7-1-repeatability-opm.md
├── chapter-7-2-data-opm.md
├── chapter-7-3-weighted-regr-opm.md
├── chapter-7-4-univariate-opm.md
├── chapter-7-5-bivariate-opm.md
├── chapter-8-1-baby-delivering-storks-example.md
└── chapter-8-2-step-step-guide-phylogenetic-path-analysis-using-d-sep-method-rhinograds-example.md
├── iframe
├── Chapter10_OPM
│ ├── OPM_chap10.doc
│ ├── OPM_chap10.pdf
│ ├── Primates.trees
│ └── Primates.txt
├── Chapter11_OPM
│ ├── 1_simple.html
│ ├── 2_multi.html
│ ├── 3_fisher.html
│ ├── 4_nongaussian.html
│ ├── 5_missing.html
│ ├── VCV.png
│ ├── biblio.html
│ ├── data.zip
│ ├── fixed.png
│ ├── funnel.png
│ ├── img1.png
│ ├── img10.png
│ ├── img11.old
│ ├── img11.png
│ ├── img12.png
│ ├── img13.png
│ ├── img14.png
│ ├── img15.png
│ ├── img16.png
│ ├── img17.png
│ ├── img2.png
│ ├── img3.png
│ ├── img4.png
│ ├── img5.png
│ ├── img6.png
│ ├── img7.png
│ ├── img8.old
│ ├── img8.png
│ ├── img9.old
│ ├── img9.png
│ ├── internals.pl
│ ├── labels.pl
│ ├── opm.css
│ └── opm.html
├── Chapter12_OPM
│ ├── 1_multi_predictors_OUT.html
│ ├── 1_multi_predictors_OUT_corr.html
│ ├── 2_phylo_uncertainity_OUT.html
│ ├── 3_weights_OUT.html
│ ├── 4_weight&lambda_OUT.html
│ ├── download
│ │ ├── 10kTrees_Primates.nex
│ │ ├── consensusTre_Primates.nex
│ │ ├── primate_data.txt
│ │ ├── primate_spec.txt
│ │ └── primate_tree.nex
│ └── figure
│ │ ├── unnamed-chunk-2.png
│ │ ├── unnamed-chunk-4.png
│ │ ├── unnamed-chunk-7.png
│ │ └── unnamed-chunk-9.png
├── Chapter13_OPM
│ ├── 1_Trees.html
│ ├── 2_Traits.html
│ ├── 3_Trees_and_traits.html
│ └── figure
│ │ ├── unnamed-chunk-15.png
│ │ └── unnamed-chunk-16.png
├── Chapter17_OPM
│ ├── download
│ │ └── ABC_PCM.c
│ ├── figure
│ │ └── image001.png
│ └── html_frame_chap17.html
├── Chapter19_OPM
│ ├── 1_Calculating_community_phylogenetic_metrics_OPM.html
│ └── download
│ │ ├── figures.R
│ │ ├── functions.R
│ │ ├── metrics.R
│ │ ├── pglmm.R
│ │ └── tables.pdf
├── Chapter21_OPM
│ ├── download
│ │ ├── BayesModelS_v22.R
│ │ ├── e.IMI.TreeBlock_10kTrees_Primates_Version3.nex.txt
│ │ └── e.dataIMI_corrected.csv
│ ├── figures for IMI OPM
│ │ ├── Thumbs.db
│ │ ├── unnamed-chunk-2.png
│ │ ├── unnamed-chunk-31.png
│ │ ├── unnamed-chunk-32.png
│ │ ├── unnamed-chunk-33.png
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│ │ └── unnamed-chunk-35.png
│ └── html_frame_chap21.html
├── Chapter22_OPM
│ ├── figure
│ │ ├── unnamed-chunk-10.png
│ │ ├── unnamed-chunk-11.png
│ │ ├── unnamed-chunk-13.png
│ │ ├── unnamed-chunk-14.png
│ │ ├── unnamed-chunk-17.png
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│ │ ├── unnamed-chunk-8.png
│ │ └── unnamed-chunk-9.png
│ └── html_frame_chap22_OUT.html
├── Chapter2_OPM
│ ├── download
│ │ ├── bird_trees.tre
│ │ ├── primate_spec.txt
│ │ └── primate_tree.phy
│ ├── figure
│ │ ├── unnamed-chunk-10.png
│ │ ├── unnamed-chunk-11.png
│ │ ├── unnamed-chunk-17.png
│ │ ├── unnamed-chunk-181.png
│ │ ├── unnamed-chunk-182.png
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│ │ ├── unnamed-chunk-63.png
│ │ ├── unnamed-chunk-64.png
│ │ ├── unnamed-chunk-7.png
│ │ └── unnamed-chunk-9.png
│ └── html_frame_chap2_OUT.html
├── Chapter4_OPM
│ ├── Centrarchidae.tre
│ ├── Revell_Chapter4_OPM_mod1.html
│ ├── anole.data.csv
│ ├── elopomorph.csv
│ └── elopomorph.tre
├── Chapter5_OPM
│ ├── OPM_chap5.pdf
│ └── download
│ │ └── vcv2phylo.R
├── Chapter6_OPM
│ ├── download
│ │ ├── covariates.txt
│ │ ├── fict_phylo.nex
│ │ └── pgls_check_fncs.r
│ ├── figure
│ │ ├── unnamed-chunk-1.png
│ │ ├── unnamed-chunk-31.png
│ │ ├── unnamed-chunk-32.png
│ │ ├── unnamed-chunk-33.png
│ │ ├── unnamed-chunk-34.png
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│ │ ├── unnamed-chunk-62.png
│ │ ├── unnamed-chunk-63.png
│ │ └── unnamed-chunk-64.png
│ └── html_frame_chap6.html
├── Chapter7_OPM
│ ├── 1_repeatability_OPM.html
│ ├── 2_data_OPM.html
│ ├── 3_weighted_regr_OPM.html
│ ├── 4_univariate_OPM.html
│ ├── 5_bivariate_OPM.html
│ ├── download
│ │ ├── GLSME.R
│ │ ├── primate_ind.txt
│ │ ├── primate_spec.txt
│ │ └── primate_tree.phy
│ └── figure
│ │ ├── unnamed-chunk-1.png
│ │ ├── unnamed-chunk-2.png
│ │ ├── unnamed-chunk-3.png
│ │ ├── unnamed-chunk-4.png
│ │ └── unnamed-chunk-6.png
└── Chapter8_OPM
│ ├── Rhinograds example.html
│ ├── Storks example.html
│ └── download
│ ├── rhino.csv
│ ├── rhino.tree
│ └── storks.csv
├── online-practical-material-chapter-11.md
├── online-practical-material-chapter-12.md
├── online-practical-material-chapter-13.md
├── online-practical-material-chapter-17.md
├── online-practical-material-chapter-19.md
├── online-practical-material-chapter-21.md
├── online-practical-material-chapter-22.md
├── online-practical-material-chapter-4.md
├── online-practical-material-chapter-5.md
├── online-practical-material-chapter-6.md
├── online-practical-material-chapter-7.md
└── online-practical-material-chapter-8.md
/.gitignore:
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1 | # History files
2 | .Rhistory
3 | .Rapp.history
4 |
5 | # Session Data files
6 | .RData
7 |
8 | # Example code in package build process
9 | *-Ex.R
10 |
11 | # Output files from R CMD build
12 | /*.tar.gz
13 |
14 | # Output files from R CMD check
15 | /*.Rcheck/
16 |
17 | # RStudio files
18 | .Rproj.user/
19 |
20 | # produced vignettes
21 | vignettes/*.html
22 | vignettes/*.pdf
23 |
24 | # OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
25 | .httr-oauth
26 |
27 | # knitr and R markdown default cache directories
28 | /*_cache/
29 | /cache/
30 |
31 | # Temporary files created by R markdown
32 | *.utf8.md
33 | *.knit.md
34 |
35 | # Shiny token, see https://shiny.rstudio.com/articles/shinyapps.html
36 | rsconnect/
37 |
38 | # Nova editors files
39 | .nova
40 | /.DS_Store
41 | .DS_Store
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/abstracts/01-introduction-phylogenetic-comparative-method.md:
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1 | # Chapter 1: An Introduction to the Phylogenetic Comparative Method"
2 |
3 | by **Emmanuel Paradis**
4 |
5 | **Abstract**
6 |
7 | The phylogenetic comparative method has an important place in evolutionary biology. This chapter aims at giving an overview on some selected topics. We first review briefly some important historical milestones including some early contributions and the relationships of comparative methods with phylogenetics. Some fundamental points on statistical inference, adaptation, and causality are then discussed. We also discuss briefly the application of the phylogenetic comparative method to anthropology, and conclude with some perspectives on its future development and applications.
8 |
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/abstracts/02-working-tree-life-comparative-studies-build-tailor-phylogenies-interspecific-datasets.md:
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1 | # Chapter 2: Working with the Tree of Life in Comparative Studies: How to Build and Tailor Phylogenies to Interspecific Datasets
2 |
3 | by **László Zsolt Garamszegi** and **Alejandro Gonzalez-Voyer**
4 |
5 | **Abstract**
6 |
7 | All comparative analyses rely on at least one phylogenetic hypothesis. However, the reconstruction of the evolutionary history of species is not the primary aim of these studies. In fact, it is rarely the case that a well-resolved, fully matching phylogeny is available for the interspecific trait data at hand. Therefore, phylogenetic information usually needs to be combined across various sources that often rely on different approaches and different markers for the phylogenetic reconstruction. Building hypotheses about the evolutionary history of species is a challenging task, as it requires knowledge about the underlying methodology and an ability to flexibly manipulate data in diverse formats. Although most practitioners are not experts in phylogenetics, the appropriate handling of phylogenetic information is crucial for making evolutionary inferences in a comparative study, because the results will be proportional to the underlying phylogeny. In this chapter we provide an overview on how to interpret and combine phylogenetic information from different sources, and review the various tree-tailoring techniques by touching upon issues that are crucial for the understanding of other chapters in this book. We conclude that whichever method is used to generate trees, the phylogenetic hypotheses will always include some uncertainty that should be taken into account in a comparative study.
8 |
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/abstracts/03-introduction-supertree-construction-partitioned-phylogenetic-analyses-view-toward-distinction-gene-trees-species-trees.md:
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1 | # Chapter 3: An Introduction to Supertree Construction (and Partitioned Phylogenetic Analyses) with a View toward the Distinction between – Gene Trees and Species Trees
2 |
3 | by **Olaf R. P. Bininda-Emonds**
4 |
5 | **Abstract**
6 |
7 | The dominant approach to the analysis of phylogenomic data is the concatenation of the individual gene data sets into a giant supermatrix that is analyzed en masse. Nevertheless, there remain compelling arguments for a partitioned approach in which individual partitions (usually genes) are instead analyzed separately and the resulting trees are combined to yield the final phylogeny. For instance, it has been argued that this supertree framework, which remains controversial, can better account for natural evolutionary processes like horizontal gene transfer and incomplete lineage sorting that can cause the gene trees, although accurate for the evolutionary history of the genes, to differ from the species tree. In this chapter, I review the different methods of supertree construction (broadly defined), including newer model-based methods based on a multispecies coalescent model. In so doing, I elaborate on some of their strengths and weaknesses relative to one another as well as provide a rough guide to performing a supertree analysis before addressing criticisms of the supertree approach in general. In the end, however, rather than dogmatically advocating supertree construction and partitioned analyses in general, I instead argue that a combined, “global congruence” approach in which data sets are analyzed under both a supermatrix (unpartitioned) and supertree (partitioned) framework represents the best strategy in our attempts to uncover the Tree of Life.
8 |
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/abstracts/04-graphical-methods-visualizing-comparative-data-phylogenies.md:
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1 | # Chapter 4: Graphical Methods for Visualizing Comparative Data on Phylogenies
2 |
3 | by **Liam J. Revell**
4 |
5 | **Abstract**
6 |
7 | Phylogenies have emerged as central in evolutionary biology over the past three decades or more, and an extraordinary expansion in the breadth and sophistication of phylogenetic comparative methods has played a large role in this growth. In this chapter I focus on a somewhat neglected area: the use of graphical methods to simultaneously represent comparative data and trees. As this research area is theoretically very broad, I have concentrated on new methods developed by me, or techniques devised by others and implemented by me as part of my R phylogenetics package, phytools. I describe a variety of methods in this chapter, including approaches that can be used to map reconstructed discrete or continuous character evolution on trees; techniques for projecting phylogenetic trees into morphospace; and methods for visualizing phylogenies in the context of a global or regional geographic map. In this chapter my intention is not merely to showcase new methods that I have developed. Rather, I have also dedicated considerable attention to detailing the algorithms and computational techniques required for these approaches with the hope that this chapter will become a resource or jumping-off point for researchers interested in building new, more advanced approaches and methods in this area.
8 |
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/abstracts/06-statistical-issues-assumptions-phylogenetic-generalised-least-squares.md:
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1 | # Chapter 6: Statistical Issues and Assumptions of Phylogenetic Generalised Least Squares
2 |
3 | by **Roger Mundry**
4 |
5 | **Abstract**
6 |
7 | Using Phylogenetic Generalised Least Squares (PGLS) means to fit a linear regression aiming to investigate the impact of one or several predictor variables on a single response variable while controlling for potential phylogenetic signal in the response (and, hence, non-independence of the residuals). The key difference between PGLS and standard (multiple) regression is that PGLS allows to control for residuals being potentially non-independent due to the phylogenetic history of the taxa investigated. While the assumptions of PGLS regarding the underlying processes of evolution and the correlation of the predictor and response variables with the phylogeny have received considerable attention, much less focus has been put on the checks of model reliability and stability commonly used in case of standard general linear models. However, several of these checks could be similarly applied in the context of PGLS as well. Here I describe how such checks of model stability and reliability could be applied in the context of a PGLS and what could be done in case they reveal potential problems. Besides treating general questions regarding the conceptual and technical validity of the model, I consider issues regarding the sample size, collinearity among the predictors, the distribution of the predictors and the residuals, model stability and drawing inference based on P-values. Finally, I emphasize the need for reporting checks of assumptions (and their results) in publications.
8 |
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/abstracts/07-uncertainties-due-within-species-variation-comparative-studies-measurement-errors-statistical-weights.md:
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1 | # Chapter 7: Uncertainties due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights
2 |
3 | by **László Zsolt Garamszegi**
4 |
5 | **Abstract**
6 |
7 | Comparative studies investigating evolutionary questions are generally concerned with interspecific variation of trait values, while variations observed within species are inherently assumed to be unimportant. However, beside measurement errors, several biological mechanisms (such as behaviors that flexibly change within individuals, differences between sexes or other groups of individuals, spatial or temporal variations across populations of the same species) can generate considerable variation in the focal characters at the within-species level. Such within-species variations can raise uncertainties and biases in parameters estimates, especially when the data are hierarchically structured along a phylogeny, thus they require appropriate statistical treatment. This chapter reviews different analytical solutions that have been recently developed to account for the unwanted effect of within-species variation. However, I will also emphasize that within-species variation should not necessarily be regarded as a confounder, but in some cases it can be subject to evolutionary forces and delineate interesting biological questions. The argumentation will be accompanied with a detailed practical material that will help users adopt the methodology to the data at hand.
8 |
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/abstracts/08-introduction-phylogenetic-path-analysis.md:
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1 | # Chapter 8: An Introduction to Phylogenetic Path Analysis
2 |
3 | by **Alejandro Gonzalez-Voyer** and **Achaz von Hardenberg**
4 |
5 | **Abstract**
6 |
7 | The questions addressed by macroevolutionary biologists are often impervious to experimental approaches and alternative methods have to be adopted. The phylogenetic comparative approach is a very powerful one since it combines a large number of species and thus spans long periods of evolutionary change. However, there are limits to the inferences that can be drawn from the results, in part due to the limitations of the most commonly employed analytical methods. In this chapter we show how confirmatory path analysis can be undertaken explicitly controlling for non-independence due to shared ancestry. The phylogenetic path analysis method we present allows researchers to move beyond the estimation of direct effects and analyze the relative importance of alternative causal models including direct and indirect paths of influence among variables. We begin the chapter with a general introduction to path analysis and then present a step-by-step guide to phylogenetic path analysis using the d-sep method. We also show how the known statistical problems associated with non-independence of data points due to shared ancestry become compounded in path analysis. We finish with a discussion about the potential effects of collinearity and measurement error, and a look towards possible future developments.
8 |
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/abstracts/09-phylogenetic-logistic-regression-binary-dependent-variables.md:
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1 | # Chapter 9: Phylogenetic Logistic Regression for Binary Dependent Variables
2 |
3 | by **Anthony R. Ives** and **Theodore Garland Jr.**
4 |
5 | **Abstract**
6 |
7 | We compare three methods for phylogenetic regression analyses designed for binary dependent variables (traits with two discrete states) both with each other and with "standard" methods that either ignore phylogenetic relationships or ignore the binary character of the dependent variable. In simulations designed to reveal statistical problems arising in different methods, PLogReg performed better than PGLMM and MCMCglmm to identify phylogenetic signal in the absence of independent variables; PLogReg also outperformed a standard method for detecting phylogenetic signal in binary data, ancestral character estimation. All three phylogenetic methods performed similarly for identifying relationships with a continuously valued independent variable x, with all methods having at most moderately inflated Type I error rates, and MCMCglmm having slightly greater power. In contrast, standard logistic regression that ignores phylogeny had seriously inflated Type I errors when x had phylogenetic signal. Perhaps surprisingly, phylogenetic regression that ignored the binary nature of the dependent variable, RegOU, performed as well or better than the other methods, at least for larger sample sizes (≥64 species), although this approach does not result in a model that can be used to simulate data (e.g., for bootstrapping). We also apply the methods to a data set describing whether antelopes fight or flee versus hide from predators as a function of their group size. We end with rough guidelines for analyzing binary dependent variables, with the main recommendation being that multiple methods and simulations should be used to give confidence in the statistical results.
8 |
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/abstracts/11-general-quantitative-genetic-methods-comparative-biology.md:
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1 | # Chapter 11: General Quantitative Genetic Methods for Comparative Biology
2 |
3 | by **Pierre de Villemereuil** and **Shinichi Nakagawa**
4 |
5 | **Abstract**
6 |
7 | There is much in common between the aim and tools of the quantitative geneticist and the comparative biologist. One of the most interesting statistical tool of the quantitative genetics is the mixed model framework, especially the so-called animal model, which can be used for comparative analyses. In this chapter, we describe the Phylogenetic Generalised Linear Mixed Model (PGLMM), which encompasses Phylogenetic (Linear) Mixed Models (PMM). The widely used Phylogenetic Generalised Least Square (PGLS) can be seen as a special case of PGLMM. Thus, we demonstrate how PGLMM can be a useful extension of PGLS, hence a useful tool for the comparative biologist. Especially, we show how the PGLMM can tackle issues such as (i) intra-specific variance inference, (ii) phylogenetic meta-analysis, (iii) non-Gaussian traits analysis, and (iv) missing values and data augmentation. Further possible extensions of the PGLMM and applications to phylogenetic comparative analysis are discussed at the end of the chapter. We provide working examples, using the R package MCMCglmm, in the Online Practical Material (OPM).
8 |
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/abstracts/12-multimodel-inference-comparative-analyses.md:
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1 | # Chapter 12: Multimodel-Inference in Comparative Analyses
2 |
3 | by **László Zsolt Garamszegi** and **Roger Mundry**
4 |
5 | **Abstract**
6 |
7 | Multimodel inference refers to the task of making a generalization from several statistical models that correspond to different biological hypotheses and that vary in the degree of how they fit the data at hand. Several approaches have been developed for such purpose, and these are widely used, mostly for intraspecific data, i.e. in a non-phylogenetic framework, to make inferences from models that consider different predictor variables in different combinations. Adding the phylogenetic component, in theory, calls for a more extended exploitation of these techniques as several hypotheses about the phylogenetic history of species and about the mode of evolution should be considered, all of which can be flexibly incorporated and combined with different statistical models. Here we highlight some biological problems that inherently imply multimodel approaches and show how these problems can be tackled in the PGLS (phylogenetic generalized least squares) modeling framework based on information-theoretic approaches (e.g., by using Akaike’s information criterion, AIC) or maximum likelihood. We present a conceptual framework of model selection for phylogenetic comparative analyses, where the goal is to generalize across models that involve different combinations of predictors, phylogenetic hypotheses, parameters describing the mode of evolution, and error structures. Although this overview suggests that model selection strategy may be useful in several situations, we note that the performance of the approach in the phylogenetic context awaits further evaluation in simulation studies.
8 |
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/abstracts/13-simulation-phylogenetic-data.md:
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1 | # Chapter 13: Simulation of Phylogenetic Data
2 |
3 | by **Emmanuel Paradis**
4 |
5 | **Abstract**
6 |
7 | Simulating phylogenetic data is a powerful tool for evolutionists, but this can be a complicated task. This chapter gives an overview on the methods to simulate species traits, particularly on a phylogeny. We show that building from three fundamental models (Brownian motion, Ornstein--Uhlenbeck, and Markov chains), many biologically relevant scenarios can be simulated. We also review briefly the simulation of phylogenies and the available software for phylogenetic data simulation. The on-line materials give several examples, including some complex cases, using R.
8 |
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/abstracts/14-use-misuse-comparative-methods-study-adaptation.md:
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1 | # Chapter 14: Use and Misuse of Comparative Methods in the Study of Adaptation
2 |
3 | by **Thomas F. Hansen**
4 |
5 | **Abstract**
6 |
7 | The comparative method can be used to test hypotheses of adaptation by comparing groups of species that meet different adaptive challenges. This requires attention to phylogenetic correlations and to historical lags in achieving adaptation. The modern phylogenetic comparative method has provided some partial solutions to these problems, but the field has also suffered from a systemic lack of demand for biological justifications of its statistical procedures. Consequently, assumptions have been made for statistical convenience and are often inconsistent with the relevant biology. I argue that common comparative tests of adaptation, including Brownian-motion-based phylogenetic linear models and inferred-changes methods based on reconstructing ancestral states, violate essential characteristics of adaptation as a biological process. I discuss the requirements for biologically consistent comparative analysis of adaptation, and I review work towards this goal.
8 |
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/abstracts/15-modelling-stabilising-selection-attraction-ornstein-uhlenbeck-models.md:
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1 | # Chapter 15: Modelling Stabilising Selection: the Attraction of Ornstein-Uhlenbeck Models
2 |
3 | by **Brian C. O’Meara** and **Jeremy M. Beaulieu**
4 |
5 | **Abstract**
6 |
7 | Ornstein-Uhlenbeck models are a generalization of Brownian motion models that allow trait values to evolve to follow optima. They have become broadly popular in evolutionary studies due to their ability to better fit empirical data as well as for the biological conclusions which can be drawn based on their parameter estimates, especially optimum trait values. We include a survey of available software implementing these models in phylogenetics as well as cautions regarding the use of this software.
8 |
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/abstracts/16-hidden-markov-models-studying-evolution-binary-morphological-characters.md:
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1 | # Chapter 16: Hidden Markov Models for Studying the Evolution of Binary Morphological Characters
2 |
3 | by **Jeremy M. Beaulieu** and **Brian C. O’Meara**
4 |
5 | **Abstract**
6 |
7 | Biologists now have the capability of building large phylogenetic trees consisting of tens of thousands of species, from which important comparative questions can be addressed. However, to the extent that biologists have applied these large trees to comparative data, it is clear that current methods, such as those that deal with the evolution of binary morphological characters, make unrealistic assumptions about how these characters are modeled. As phylogenies increase both in size and scope it is likely that the lability of a binary character will differ significantly among lineages. In this chapter we describe how a new generalized model, which we refer to as the "hidden rates model" (HRM), can be used to identify different rates of evolution in a discrete binary character along different branches of a phylogeny. The HRM is part of a class of models that are more broadly known as Hidden Markov models because it presupposes that unobserved "hidden" rate classes underlie each observed state, and that each rate class represents potentially different transition rates to and from these observed states. As we discuss, the recognition and accommodation of this heterogeneity can provide a robust picture of binary character evolution.
8 |
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/abstracts/17-detecting-phenotypic-selection-approximate-bayesian-computation-abc-phylogenetic-comparative-methods.md:
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1 | # Chapter 17: Detecting Phenotypic Selection by Approximate Bayesian Computation (ABC) in Phylogenetic Comparative Methods
2 |
3 | by **Nobuyuki Kutsukake** and **Hideki Innan**
4 |
5 | **Abstract**
6 |
7 | This chapter discusses the fundamental structure and advantages of the approximate Bayesian computation (ABC) algorithm in phylogenetic comparative methods (PCMs). ABC estimates unknown parameters as follows: (i) simulated data are generated under a suite of parameters randomly chosen from their prior distributions; (ii) the simulated data are compared with empirical data; (iii) parameters are accepted when the distance between the simulated and empirical data is small; and (iv) by repeating steps (i) to (iii), posterior distributions of parameters will be gained. Because ABC does not necessitate mathematical expression or analytic solution of a likelihood function, ABC is particularly useful when a maximum-likelihood estimation is difficult to conduct (a common situation when testing complex evolutionary models and/or models with many parameters in PCMs). As an application, we analysed trait evolution in which a specific species exhibits an extraordinary trait value relative to others. The ABC approach detected the occurrence of branch-specific directional selection and estimated ancestral states of internal nodes. As computational power increases, such likelihood-free approaches will become increasingly useful for PCMs, particularly for testing complex evolutionary models that deviate from the standard models based on the Brownian motion.
8 |
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/abstracts/18-phylogenetic-comparative-methods-studying-clade-wide-convergence.md:
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1 | # Chapter 18: Phylogenetic Comparative Methods for Studying Clade-Wide Convergence
2 |
3 | by **D. Luke Mahler** and **Travis Ingram**
4 |
5 | **Abstract**
6 |
7 | A recurring question in ecology and evolutionary biology is whether deterministic evolutionary convergence ever occurs among large sets of species, such as ecological communities or entire evolutionary radiations. Questions about large-scale convergence have featured prominently in discussions of the nature of community assembly, and in debates about the relative roles of contingency versus determinism in macroevolution. Until recently, however, there have been relatively few attempts to use a phylogenetic comparative approach to answer questions about clade-level convergence. This is beginning to change with the development of new and more flexible comparative techniques for studying macroevolutionary convergence. In this chapter, we discuss ecological and evolutionary questions that have motivated interest in convergence at large spatial and phylogenetic scales. We review the statistical approaches that have been used to investigate clade-wide convergence, and then describe SURFACE, a recently developed method for objectively studying convergence using macroevolutionary adaptive landscape models. We introduce new features within this framework for testing hypotheses about the biogeography of large-scale convergence, and for visualizing the relative contributions of different traits to multidimensional convergence, and demonstrate these features using convergent Caribbean _Anolis_ lizard faunas. We conclude by discussing the limitations of current approaches for studying clade-wide convergence, and highlighting some directions for future research.
8 |
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/abstracts/19-metrics-models-community-phylogenetics.md:
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1 | # Chapter 19: Metrics and Models of Community Phylogenetics
2 |
3 | by **William D. Pearse**, **Andy Purvis**, **Jeannine Cavender-Bares** and **Matthew R. Helmus**
4 |
5 | **Abstract**
6 |
7 | Community phylogenetics combines ideas from community ecology and evolutionary biology, using species’ phylogeny to explore the processes underlying ecological community assembly. Here we describe the development of the field's comparative methods and their roots in conservation biology, biodiversity quantification, and macroevolution. Next, we review the multitude of community phylogenetic structure metrics and place each into one of four classes: shape, evenness, dispersion, and dissimilarity. Shape metrics examine the structure of an assemblage phylogeny, while evenness metrics incorporate species’ abundances. Dispersion metrics examine assemblages given a phylogeny of species that could occupy that assemblage (the source pool), while dissimilarity metrics compare phylogenetic structure between assemblages. We then examine how metrics perform in simulated communities that vary in their phylogenetic structure. We provide an example of model-based approaches, and argue that they are a promising area of future research in community phylogenetics. Code to reproduce all these analyses is available in the Online Practical Material. We conclude by discussing future research directions for the field as a whole.
8 |
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/abstracts/20-event-based-cophylogenetic-comparative-analysis.md:
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1 | # Chapter 20: Event-Based Cophylogenetic Comparative Analysis
2 |
3 | by **Michael Charleston** and **Ran Libeskind-Hadas**
4 |
5 | **Abstract**
6 |
7 | Cophylogenetic analysis seeks to explain the relationships between mutually evolving pairs of species such as hosts and parasites. In the last two decades, increasingly sophisticated computational methods have been developed for performing cophylogenetic analyses. In particular, event-based reconstruction methods attempt to find the best supported reconstructions of pairs of related trees using a set of events including cospeciation, duplication, transfer, and loss. This chapter formulates the cophylogeny reconstruction problem, describes the algorithmic techniques that have been developed for this problem, and compares and contrasts the software packages that implement these methods.
8 |
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/abstracts/21-phylogenetic-prediction-identify-evolutionary-singularities.md:
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1 | # Chapter 21: Phylogenetic Prediction to Identify “Evolutionary Singularities”
2 |
3 | by **Charles L. Nunn** and **Li Zhu**
4 |
5 | ****Abstract****
6 |
7 | Understanding adaptive patterns is especially difficult in the case of “evolutionary singularities,” i.e. traits that evolved in only one lineage in the clade of interest. New methods are needed to integrate our understanding of general phenotypic correlations and convergence within a clade when examining a single lineage in that clade. Here, we develop and apply a new method to investigate change along a single branch of an evolutionary tree; this method can be applied to any branch on a phylogeny, typically focusing on an _a priori_ hypothesis for “exceptional evolution” along particular branches, for example in humans relative to other primates. Specifically, we use phylogenetic methods to predict trait values for a tip on the phylogeny based on a statistical (regression) model, phylogenetic signal (l), and evolutionary relationships among species in the clade. We can then evaluate whether the observed value departs from the predicted value. We provide two worked examples in human evolution using original R scripts that implement this concept in a Bayesian framework. We also provide simulations that investigate the statistical validity of the approach. While multiple approaches can and should be used to investigate singularities in an evolutionary context – including studies of the rate of phenotypic change along a branch – our Bayesian approach provides a way to place confidence on the predicted values in light of uncertainty about the underlying evolutionary and statistical parameters.
8 |
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1 | # Chapter 22: Preparing Paleontological Datasets for Phylogenetic Comparative Methods
2 |
3 | by **David W. Bapst**
4 |
5 | **Abstract**
6 |
7 | The fossil record holds considerable promise for furthering our understanding of macroevolutionary patterns, particularly allowing us to analyze hypotheses which cannot be tested with phylogenies of extant taxa alone. However, although there is a growing number of paleontological studies that use phylogenetic comparative methods to address questions of trait evolution, there is little documentation on obtaining the time-scaled phylogenies of fossil taxa required for such analyses. This chapter is an attempt to introduce interested readers to the issues involved with that process, including the uncertainties and biases involved with fossil data, which some might inadvertently overlook. In addition, I illustrate how the fossil records of different groups can be very different in terms of the datasets available, including the issues of that data, and stress that there is no ‘one size fits all’ solution. Instead, for several hypothetical examples, I recommend several approaches that explicitly consider potential uncertainties, unavailable data and biasing factors.
8 |
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1 | Figures for Chapter 10.
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1 | Figures for Chapter 11.
2 |
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1 | Figures for Chapter 2.
2 |
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1 | Figures for Chapter 4.
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1 | Figures for Chapter 5.
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1 | Figures for Chapter 6.
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1 | Figures for Chapter 7.
2 |
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1 | Figures for Chapter 8.
2 |
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/backup/book-sections.md:
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1 | ---
2 | title: "Book sections"
3 | date: "2014-06-12"
4 | ---
5 |
6 |
7 |
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/backup/book/CHAPTERS/1-introduction-phylogenetic-comparative-method.md:
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1 | ---
2 | title: "Chapter 1: An Introduction to the Phylogenetic Comparative Method"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Emmanuel Paradis**
7 |
8 | **Abstract**
9 |
10 | The phylogenetic comparative method has an important place in evolutionary biology. This chapter aims at giving an overview on some selected topics. We first review briefly some important historical milestones including some early contributions and the relationships of comparative methods with phylogenetics. Some fundamental points on statistical inference, adaptation, and causality are then discussed. We also discuss briefly the application of the phylogenetic comparative method to anthropology, and conclude with some perspectives on its future development and applications.
11 |
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/backup/book/CHAPTERS/11-general-quantitative-genetic-methods-comparative-biology.md:
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1 | ---
2 | title: "Chapter 11: General Quantitative Genetic Methods for Comparative Biology"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Pierre de Villemereuil** and **Shinichi Nakagawa**
7 |
8 | **Abstract**
9 |
10 | There is much in common between the aim and tools of the quantitative geneticist and the comparative biologist. One of the most interesting statistical tool of the quantitative genetics is the mixed model framework, especially the so-called animal model, which can be used for comparative analyses. In this chapter, we describe the Phylogenetic Generalised Linear Mixed Model (PGLMM), which encompasses Phylogenetic (Linear) Mixed Models (PMM). The widely used Phylogenetic Generalised Least Square (PGLS) can be seen as a special case of PGLMM. Thus, we demonstrate how PGLMM can be a useful extension of PGLS, hence a useful tool for the comparative biologist. Especially, we show how the PGLMM can tackle issues such as (i) intra-specific variance inference, (ii) phylogenetic meta-analysis, (iii) non-Gaussian traits analysis, and (iv) missing values and data augmentation. Further possible extensions of the PGLMM and applications to phylogenetic comparative analysis are discussed at the end of the chapter. We provide working examples, using the R package MCMCglmm, in the Online Practical Material (OPM).
11 |
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/backup/book/CHAPTERS/12-multimodel-inference-comparative-analyses.md:
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1 | ---
2 | title: "Chapter 12: Multimodel-Inference in Comparative Analyses"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **László Zsolt Garamszegi** and **Roger Mundry**
7 |
8 | **Abstract**
9 |
10 | Multimodel inference refers to the task of making a generalization from several statistical models that correspond to different biological hypotheses and that vary in the degree of how they fit the data at hand. Several approaches have been developed for such purpose, and these are widely used, mostly for intraspecific data, i.e. in a non-phylogenetic framework, to make inferences from models that consider different predictor variables in different combinations. Adding the phylogenetic component, in theory, calls for a more extended exploitation of these techniques as several hypotheses about the phylogenetic history of species and about the mode of evolution should be considered, all of which can be flexibly incorporated and combined with different statistical models. Here we highlight some biological problems that inherently imply multimodel approaches and show how these problems can be tackled in the PGLS (phylogenetic generalized least squares) modeling framework based on information-theoretic approaches (e.g., by using Akaike’s information criterion, AIC) or maximum likelihood. We present a conceptual framework of model selection for phylogenetic comparative analyses, where the goal is to generalize across models that involve different combinations of predictors, phylogenetic hypotheses, parameters describing the mode of evolution, and error structures. Although this overview suggests that model selection strategy may be useful in several situations, we note that the performance of the approach in the phylogenetic context awaits further evaluation in simulation studies.
11 |
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/backup/book/CHAPTERS/13-simulation-phylogenetic-data.md:
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1 | ---
2 | title: "Chapter 13: Simulation of Phylogenetic Data"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Emmanuel Paradis**
7 |
8 | **Abstract**
9 |
10 | Simulating phylogenetic data is a powerful tool for evolutionists, but this can be a complicated task. This chapter gives an overview on the methods to simulate species traits, particularly on a phylogeny. We show that building from three fundamental models (Brownian motion, Ornstein--Uhlenbeck, and Markov chains), many biologically relevant scenarios can be simulated. We also review briefly the simulation of phylogenies and the available software for phylogenetic data simulation. The on-line materials give several examples, including some complex cases, using R.
11 |
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/backup/book/CHAPTERS/14-use-misuse-comparative-methods-study-adaptation.md:
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1 | ---
2 | title: "Chapter 14: Use and Misuse of Comparative Methods in the Study of Adaptation"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Thomas F. Hansen**
7 |
8 | **Abstract**
9 |
10 | The comparative method can be used to test hypotheses of adaptation by comparing groups of species that meet different adaptive challenges. This requires attention to phylogenetic correlations and to historical lags in achieving adaptation. The modern phylogenetic comparative method has provided some partial solutions to these problems, but the field has also suffered from a systemic lack of demand for biological justifications of its statistical procedures. Consequently, assumptions have been made for statistical convenience and are often inconsistent with the relevant biology. I argue that common comparative tests of adaptation, including Brownian-motion-based phylogenetic linear models and inferred-changes methods based on reconstructing ancestral states, violate essential characteristics of adaptation as a biological process. I discuss the requirements for biologically consistent comparative analysis of adaptation, and I review work towards this goal.
11 |
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/backup/book/CHAPTERS/15-modelling-stabilising-selection-attraction-ornstein-uhlenbeck-models.md:
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1 | ---
2 | title: "Chapter 15: Modelling Stabilising Selection: the Attraction of Ornstein-Uhlenbeck Models"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Brian C. O’Meara** and **Jeremy M. Beaulieu**
7 |
8 | **Abstract**
9 |
10 | Ornstein-Uhlenbeck models are a generalization of Brownian motion models that allow trait values to evolve to follow optima. They have become broadly popular in evolutionary studies due to their ability to better fit empirical data as well as for the biological conclusions which can be drawn based on their parameter estimates, especially optimum trait values. We include a survey of available software implementing these models in phylogenetics as well as cautions regarding the use of this software.
11 |
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/backup/book/CHAPTERS/16-hidden-markov-models-studying-evolution-binary-morphological-characters.md:
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1 | ---
2 | title: "Chapter 16: Hidden Markov Models for Studying the Evolution of Binary Morphological Characters"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Jeremy M. Beaulieu** and **Brian C. O’Meara**
7 |
8 | **Abstract**
9 |
10 | Biologists now have the capability of building large phylogenetic trees consisting of tens of thousands of species, from which important comparative questions can be addressed. However, to the extent that biologists have applied these large trees to comparative data, it is clear that current methods, such as those that deal with the evolution of binary morphological characters, make unrealistic assumptions about how these characters are modeled. As phylogenies increase both in size and scope it is likely that the lability of a binary character will differ significantly among lineages. In this chapter we describe how a new generalized model, which we refer to as the "hidden rates model" (HRM), can be used to identify different rates of evolution in a discrete binary character along different branches of a phylogeny. The HRM is part of a class of models that are more broadly known as Hidden Markov models because it presupposes that unobserved "hidden" rate classes underlie each observed state, and that each rate class represents potentially different transition rates to and from these observed states. As we discuss, the recognition and accommodation of this heterogeneity can provide a robust picture of binary character evolution.
11 |
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/backup/book/CHAPTERS/17-detecting-phenotypic-selection-approximate-bayesian-computation-abc-phylogenetic-comparative-methods.md:
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1 | ---
2 | title: "Chapter 17: Detecting Phenotypic Selection by Approximate Bayesian Computation (ABC) in Phylogenetic Comparative Methods"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Nobuyuki Kutsukake** and **Hideki Innan**
7 |
8 | **Abstract**
9 |
10 | This chapter discusses the fundamental structure and advantages of the approximate Bayesian computation (ABC) algorithm in phylogenetic comparative methods (PCMs). ABC estimates unknown parameters as follows: (i) simulated data are generated under a suite of parameters randomly chosen from their prior distributions; (ii) the simulated data are compared with empirical data; (iii) parameters are accepted when the distance between the simulated and empirical data is small; and (iv) by repeating steps (i) to (iii), posterior distributions of parameters will be gained. Because ABC does not necessitate mathematical expression or analytic solution of a likelihood function, ABC is particularly useful when a maximum-likelihood estimation is difficult to conduct (a common situation when testing complex evolutionary models and/or models with many parameters in PCMs). As an application, we analysed trait evolution in which a specific species exhibits an extraordinary trait value relative to others. The ABC approach detected the occurrence of branch-specific directional selection and estimated ancestral states of internal nodes. As computational power increases, such likelihood-free approaches will become increasingly useful for PCMs, particularly for testing complex evolutionary models that deviate from the standard models based on the Brownian motion.
11 |
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/backup/book/CHAPTERS/18-phylogenetic-comparative-methods-studying-clade-wide-convergence.md:
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1 | ---
2 | title: "Chapter 18: Phylogenetic Comparative Methods for Studying Clade-Wide Convergence"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **D. Luke Mahler** and **Travis Ingram**
7 |
8 | **Abstract**
9 |
10 | A recurring question in ecology and evolutionary biology is whether deterministic evolutionary convergence ever occurs among large sets of species, such as ecological communities or entire evolutionary radiations. Questions about large-scale convergence have featured prominently in discussions of the nature of community assembly, and in debates about the relative roles of contingency versus determinism in macroevolution. Until recently, however, there have been relatively few attempts to use a phylogenetic comparative approach to answer questions about clade-level convergence. This is beginning to change with the development of new and more flexible comparative techniques for studying macroevolutionary convergence. In this chapter, we discuss ecological and evolutionary questions that have motivated interest in convergence at large spatial and phylogenetic scales. We review the statistical approaches that have been used to investigate clade-wide convergence, and then describe SURFACE, a recently developed method for objectively studying convergence using macroevolutionary adaptive landscape models. We introduce new features within this framework for testing hypotheses about the biogeography of large-scale convergence, and for visualizing the relative contributions of different traits to multidimensional convergence, and demonstrate these features using convergent Caribbean _Anolis_ lizard faunas. We conclude by discussing the limitations of current approaches for studying clade-wide convergence, and highlighting some directions for future research.
11 |
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/backup/book/CHAPTERS/19-metrics-models-community-phylogenetics.md:
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1 | ---
2 | title: "Chapter 19: Metrics and Models of Community Phylogenetics"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **William D. Pearse**, **Andy Purvis**, **Jeannine Cavender-Bares** and **Matthew R. Helmus**
7 |
8 | **Abstract**
9 |
10 | Community phylogenetics combines ideas from community ecology and evolutionary biology, using species’ phylogeny to explore the processes underlying ecological community assembly. Here we describe the development of the field's comparative methods and their roots in conservation biology, biodiversity quantification, and macroevolution. Next, we review the multitude of community phylogenetic structure metrics and place each into one of four classes: shape, evenness, dispersion, and dissimilarity. Shape metrics examine the structure of an assemblage phylogeny, while evenness metrics incorporate species’ abundances. Dispersion metrics examine assemblages given a phylogeny of species that could occupy that assemblage (the source pool), while dissimilarity metrics compare phylogenetic structure between assemblages. We then examine how metrics perform in simulated communities that vary in their phylogenetic structure. We provide an example of model-based approaches, and argue that they are a promising area of future research in community phylogenetics. Code to reproduce all these analyses is available in the Online Practical Material. We conclude by discussing future research directions for the field as a whole.
11 |
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/backup/book/CHAPTERS/2-working-tree-life-comparative-studies-build-tailor-phylogenies-interspecific-datasets.md:
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1 | ---
2 | title: "Chapter 2: Working with the Tree of Life in Comparative Studies: How to Build and Tailor Phylogenies to Interspecific Datasets"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **László Zsolt Garamszegi** and **Alejandro Gonzalez-Voyer**
7 |
8 | **Abstract**
9 |
10 | All comparative analyses rely on at least one phylogenetic hypothesis. However, the reconstruction of the evolutionary history of species is not the primary aim of these studies. In fact, it is rarely the case that a well-resolved, fully matching phylogeny is available for the interspecific trait data at hand. Therefore, phylogenetic information usually needs to be combined across various sources that often rely on different approaches and different markers for the phylogenetic reconstruction. Building hypotheses about the evolutionary history of species is a challenging task, as it requires knowledge about the underlying methodology and an ability to flexibly manipulate data in diverse formats. Although most practitioners are not experts in phylogenetics, the appropriate handling of phylogenetic information is crucial for making evolutionary inferences in a comparative study, because the results will be proportional to the underlying phylogeny. In this chapter we provide an overview on how to interpret and combine phylogenetic information from different sources, and review the various tree-tailoring techniques by touching upon issues that are crucial for the understanding of other chapters in this book. We conclude that whichever method is used to generate trees, the phylogenetic hypotheses will always include some uncertainty that should be taken into account in a comparative study.
11 |
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/backup/book/CHAPTERS/20-event-based-cophylogenetic-comparative-analysis.md:
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1 | ---
2 | title: "Chapter 20: Event-Based Cophylogenetic Comparative Analysis"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Michael Charleston** and **Ran Libeskind-Hadas**
7 |
8 | **Abstract**
9 |
10 | Cophylogenetic analysis seeks to explain the relationships between mutually evolving pairs of species such as hosts and parasites. In the last two decades, increasingly sophisticated computational methods have been developed for performing cophylogenetic analyses. In particular, event-based reconstruction methods attempt to find the best supported reconstructions of pairs of related trees using a set of events including cospeciation, duplication, transfer, and loss. This chapter formulates the cophylogeny reconstruction problem, describes the algorithmic techniques that have been developed for this problem, and compares and contrasts the software packages that implement these methods.
11 |
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/backup/book/CHAPTERS/21-phylogenetic-prediction-identify-evolutionary-singularities.md:
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1 | ---
2 | title: "Chapter 21: Phylogenetic Prediction to Identify “Evolutionary Singularities”"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Charles L. Nunn** and **Li Zhu**
7 |
8 | ****Abstract****
9 |
10 | Understanding adaptive patterns is especially difficult in the case of “evolutionary singularities,” i.e. traits that evolved in only one lineage in the clade of interest. New methods are needed to integrate our understanding of general phenotypic correlations and convergence within a clade when examining a single lineage in that clade. Here, we develop and apply a new method to investigate change along a single branch of an evolutionary tree; this method can be applied to any branch on a phylogeny, typically focusing on an _a priori_ hypothesis for “exceptional evolution” along particular branches, for example in humans relative to other primates. Specifically, we use phylogenetic methods to predict trait values for a tip on the phylogeny based on a statistical (regression) model, phylogenetic signal (l), and evolutionary relationships among species in the clade. We can then evaluate whether the observed value departs from the predicted value. We provide two worked examples in human evolution using original R scripts that implement this concept in a Bayesian framework. We also provide simulations that investigate the statistical validity of the approach. While multiple approaches can and should be used to investigate singularities in an evolutionary context – including studies of the rate of phenotypic change along a branch – our Bayesian approach provides a way to place confidence on the predicted values in light of uncertainty about the underlying evolutionary and statistical parameters.
11 |
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/backup/book/CHAPTERS/22-preparing-paleontological-datasets-phylogenetic-comparative-methods.md:
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1 | ---
2 | title: "Chapter 22: Preparing Paleontological Datasets for Phylogenetic Comparative Methods"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **David W. Bapst**
7 |
8 | **Abstract**
9 |
10 | The fossil record holds considerable promise for furthering our understanding of macroevolutionary patterns, particularly allowing us to analyze hypotheses which cannot be tested with phylogenies of extant taxa alone. However, although there is a growing number of paleontological studies that use phylogenetic comparative methods to address questions of trait evolution, there is little documentation on obtaining the time-scaled phylogenies of fossil taxa required for such analyses. This chapter is an attempt to introduce interested readers to the issues involved with that process, including the uncertainties and biases involved with fossil data, which some might inadvertently overlook. In addition, I illustrate how the fossil records of different groups can be very different in terms of the datasets available, including the issues of that data, and stress that there is no ‘one size fits all’ solution. Instead, for several hypothetical examples, I recommend several approaches that explicitly consider potential uncertainties, unavailable data and biasing factors.
11 |
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/backup/book/CHAPTERS/4-graphical-methods-visualizing-comparative-data-phylogenies.md:
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1 | ---
2 | title: "Chapter 4: Graphical Methods for Visualizing Comparative Data on Phylogenies"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Liam J. Revell**
7 |
8 | **Abstract**
9 |
10 | Phylogenies have emerged as central in evolutionary biology over the past three decades or more, and an extraordinary expansion in the breadth and sophistication of phylogenetic comparative methods has played a large role in this growth. In this chapter I focus on a somewhat neglected area: the use of graphical methods to simultaneously represent comparative data and trees. As this research area is theoretically very broad, I have concentrated on new methods developed by me, or techniques devised by others and implemented by me as part of my R phylogenetics package, phytools. I describe a variety of methods in this chapter, including approaches that can be used to map reconstructed discrete or continuous character evolution on trees; techniques for projecting phylogenetic trees into morphospace; and methods for visualizing phylogenies in the context of a global or regional geographic map. In this chapter my intention is not merely to showcase new methods that I have developed. Rather, I have also dedicated considerable attention to detailing the algorithms and computational techniques required for these approaches with the hope that this chapter will become a resource or jumping-off point for researchers interested in building new, more advanced approaches and methods in this area.
11 |
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/backup/book/CHAPTERS/6-statistical-issues-assumptions-phylogenetic-generalised-least-squares.md:
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1 | ---
2 | title: "Chapter 6: Statistical Issues and Assumptions of Phylogenetic Generalised Least Squares"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Roger Mundry**
7 |
8 | **Abstract**
9 |
10 | Using Phylogenetic Generalised Least Squares (PGLS) means to fit a linear regression aiming to investigate the impact of one or several predictor variables on a single response variable while controlling for potential phylogenetic signal in the response (and, hence, non-independence of the residuals). The key difference between PGLS and standard (multiple) regression is that PGLS allows to control for residuals being potentially non-independent due to the phylogenetic history of the taxa investigated. While the assumptions of PGLS regarding the underlying processes of evolution and the correlation of the predictor and response variables with the phylogeny have received considerable attention, much less focus has been put on the checks of model reliability and stability commonly used in case of standard general linear models. However, several of these checks could be similarly applied in the context of PGLS as well. Here I describe how such checks of model stability and reliability could be applied in the context of a PGLS and what could be done in case they reveal potential problems. Besides treating general questions regarding the conceptual and technical validity of the model, I consider issues regarding the sample size, collinearity among the predictors, the distribution of the predictors and the residuals, model stability and drawing inference based on P-values. Finally, I emphasize the need for reporting checks of assumptions (and their results) in publications.
11 |
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/backup/book/CHAPTERS/7-uncertainties-due-within-species-variation-comparative-studies-measurement-errors-statistical-weights.md:
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1 | ---
2 | title: "Chapter 7: Uncertainties due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **László Zsolt Garamszegi**
7 |
8 | **Abstract**
9 |
10 | Comparative studies investigating evolutionary questions are generally concerned with interspecific variation of trait values, while variations observed within species are inherently assumed to be unimportant. However, beside measurement errors, several biological mechanisms (such as behaviors that flexibly change within individuals, differences between sexes or other groups of individuals, spatial or temporal variations across populations of the same species) can generate considerable variation in the focal characters at the within-species level. Such within-species variations can raise uncertainties and biases in parameters estimates, especially when the data are hierarchically structured along a phylogeny, thus they require appropriate statistical treatment. This chapter reviews different analytical solutions that have been recently developed to account for the unwanted effect of within-species variation. However, I will also emphasize that within-species variation should not necessarily be regarded as a confounder, but in some cases it can be subject to evolutionary forces and delineate interesting biological questions. The argumentation will be accompanied with a detailed practical material that will help users adopt the methodology to the data at hand.
11 |
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/backup/book/CHAPTERS/8-introduction-phylogenetic-path-analysis.md:
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1 | ---
2 | title: "Chapter 8: An Introduction to Phylogenetic Path Analysis"
3 | date: "2014-06-12"
4 | ---
5 |
6 | by **Alejandro Gonzalez-Voyer** and **Achaz von Hardenberg**
7 |
8 | **Abstract**
9 |
10 | The questions addressed by macroevolutionary biologists are often impervious to experimental approaches and alternative methods have to be adopted. The phylogenetic comparative approach is a very powerful one since it combines a large number of species and thus spans long periods of evolutionary change. However, there are limits to the inferences that can be drawn from the results, in part due to the limitations of the most commonly employed analytical methods. In this chapter we show how confirmatory path analysis can be undertaken explicitly controlling for non-independence due to shared ancestry. The phylogenetic path analysis method we present allows researchers to move beyond the estimation of direct effects and analyze the relative importance of alternative causal models including direct and indirect paths of influence among variables. We begin the chapter with a general introduction to path analysis and then present a step-by-step guide to phylogenetic path analysis using the d-sep method. We also show how the known statistical problems associated with non-independence of data points due to shared ancestry become compounded in path analysis. We finish with a discussion about the potential effects of collinearity and measurement error, and a look towards possible future developments.
11 |
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/backup/data_files/ch10/Primates.txt:
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1 | Cercocebus_torquatus 1 1
2 | Cercopithecus_aethiops 0 1
3 | Cercopithecus_mona 0 0
4 | Cercopithecus_nictitans 0 0
5 | Colobus_angolensis 0 1
6 | Colobus_guereza 0 0
7 | Colobus_polykomos 0 1
8 | Gorilla_gorilla 0 0
9 | Homo_sapiens 0 0
10 | Hylobates_agilis 0 0
11 | Hylobates_concolor 0 0
12 | Hylobates_gabriellae 0 0
13 | Hylobates_hoolock 0 0
14 | Hylobates_klossii 0 0
15 | Hylobates_lar 0 0
16 | Hylobates_leucogenys 0 0
17 | Hylobates_moloch 0 0
18 | Hylobates_muelleri 0 0
19 | Hylobates_pileatus 0 0
20 | Hylobates_syndactylus 0 0
21 | Macaca_brunnescens 1 1
22 | Macaca_cyclopis - 1
23 | Macaca_fascicularis - 1
24 | Macaca_hecki 1 1
25 | Macaca_maura 1 1
26 | Macaca_mulatta - 1
27 | Macaca_nemestrina 1 1
28 | Macaca_nigra 1 1
29 | Macaca_nigriscens 1 1
30 | Macaca_ochreata 1 1
31 | Macaca_silenus 1 1
32 | Macaca_sylvanus 1 1
33 | Macaca_tonkeana 1 1
34 | Mandrillus_leucophaeus 1 1
35 | Mandrillus_sphinx 1 1
36 | asalis_larvatus 0 0
37 | Pan_paniscus 1 1
38 | Pan_troglodytes 1 1
39 | Papio_anubis 1 1
40 | Papio_cynocephalus 1 1
41 | Papio_hamadryas 1 1
42 | Pongo_pygmaeus 0 0
43 | Pongo_pygmaeus_abelii 0 0
44 | Presbytis_francoisi 0 0
45 | Presbytis_phayrei 0 0
46 | Presbytis_senex 0 0
47 | Procolobus_badius 1 1
48 | Pygathrix_nemaeus 0 1
49 | Pygathrix_roxellana 0 1
50 | Rhinopithecus_avunculus 0 1
51 | Rhinopithecus_bieti 0 1
52 | Semnopithecus_entellus 0 1
53 | Trachypithecus_cristatus 0 0
54 | Trachypithecus_francoisi 0 0
55 | Trachypithecus_geei 0 0
56 | Trachypithecus_johnii 0 0
57 | Trachypithecus_phayrei 0 -
58 | Trachypithecus_pileatus 0 0
59 | Trachypithecus_vetulus 0 0
60 | Macaca_Arctoides 0 1
61 |
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/backup/data_files/ch10/ch10_data.md:
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1 | Data files for Chapter 10.
2 |
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/backup/data_files/ch11/ch11_data.md:
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1 | Data files for Chapter 11.
2 |
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/backup/data_files/ch19/tables.pdf:
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/backup/data_files/ch2/ch2_data.md:
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1 | Data files for Chapter 2.
2 |
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/backup/data_files/ch4/Centrarchidae.tre:
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1 | (Acantharchus_pomotis:0.3119231913,(((((Lepomis_gibbosus:0.07280374575,(Lepomis_microlophus:0.03213022453,(Lepomis_punctatus:0.01550794074,Lepomis_miniatus:0.01550794074):0.01662228379):0.04067352122):0.01829379836,(Lepomis_auritus:0.03890914473,(Lepomis_marginatus:0.0252584424,Lepomis_megalotis:0.0252584424):0.01365070233):0.05218839937):0.04485230765,((Lepomis_humilis:0.04800961295,Lepomis_macrochirus:0.04800961295):0.07373236495,(Lepomis_gulosus:0.06128886759,(Lepomis_symmetricus:0.02405123743,Lepomis_cyanellus:0.02405123743):0.03723763016):0.06045311031):0.01420787385):0.09444057324,((Micropterus_cataractae:0.05989593878,(Micropterus_coosae:0.05506711891,(Micropterus_notius:0.0473595795,(Micropterus_treculi:0.03816624936,(Micropterus_salmoides:0.02637278545,Micropterus_floridanus:0.02637278545):0.01179346391):0.009193330139):0.007707539409):0.004828819871):0.01810807452,(Micropterus_punctulatus:0.01550794074,Micropterus_dolomieu:0.01550794074):0.06249607256):0.1523864117):0.03835197321,(Centrarchus_macropterus:0.2120037647,((Enneacanthus_chaetodon:0.1051196941,(Enneacanthus_gloriosus:0.037423354,Enneacanthus_obesus:0.037423354):0.06769634011):0.09546205437,((Pomoxis_annularis:0.1114343047,Pomoxis_nigromaculatus:0.1114343047):0.06667485899,(Archoplites_interruptus:0.1439359769,((Ambloplites_ariommus:0.02720854273,Ambloplites_rupestris:0.02720854273):0.05488139507,(Ambloplites_cavifrons:0.06816064972,Ambloplites_constellatus:0.06816064972):0.01392928809):0.06184603912):0.03417318678):0.02247258478):0.01142201623):0.05673863348):0.04318079308);
2 |
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/backup/data_files/ch4/ch4_data.md:
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1 | Data files for Chapter 4.
2 |
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/backup/data_files/ch5/ch5_data.md:
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1 | Data files for Chapter 5.
2 |
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/backup/data_files/ch6/ch6_data.md:
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1 | Data files for Chapter 6.
2 |
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/backup/data_files/ch7/ch7_data.md:
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1 | Data files for Chapter 7.
2 |
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/backup/data_files/ch8/ch8_data.md:
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1 | Data files for Chapter 8.
2 |
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/backup/data_files/ch8/storks.csv:
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1 | Country,Area,Storks,Humans,Birth
2 | Albania,28750,100,3.2,83
Austria,83860,300,7.6,87
Belgium,30520,1,9.9,118
Bulgaria,111000,5000,9.0,117
Denmark,43100,9,5.1,59
France,544000,140,56,774
Germany,357000,3300,78,901
Greece,132000,2500,10,106
Holland,41900,4,15,188
Hungary,93000,5000,11,124
Italy,301280,5,57,551
Poland,312680,30000,38,610
Portugal,92390,1500,10,120
Romania,237500,5000,23,367
Spain,504750,8000,39,439
Switzerland,41290,150,6.7,82
Turkey,779450,25000,56,1576
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/backup/part-ii-handling-phylogenies-different-statistical-designs.md:
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1 | ---
2 | title: "Part II Handling Phylogenies in Different Statistical Designs"
3 | date: "2014-06-12"
4 | ---
5 |
6 |
7 |
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/backup/part-iii-specific-models-studying-evolutionary-mechanisms.md:
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1 | ---
2 | title: "Part III Specific Models for Studying Evolutionary Mechanisms"
3 | date: "2014-06-12"
4 | ---
5 |
6 |
7 |
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/backup/part-introduction.md:
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1 | ---
2 | title: "Part I Introduction"
3 | date: "2014-06-12"
4 | ---
5 |
6 |
7 |
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/online_practical_material/02-chapter.md:
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1 | # **Online Practical Materials**
2 |
3 | ## Chapter 2 – Working with the Tree of Life in Comparative Studies: How to Build and Tailor Phylogenies to Interspecific Datasets
4 |
5 | ### Exercises and tutorials
6 |
7 | 1) [Exercises for building and manipulating phylogenetic trees](exercises_and_tutorials/chapter-2-1-exercises-building-manipulating-phylogenetic-trees.md "Chapter 2: 1 Exercises for building and manipulating phylogenetic trees")
8 |
9 | ### Sources and example data (you need to download them to execute the materials above)
10 |
11 | 1) [primate\_tree.phy](data_files/ch2/primate_tree.phy "primate_tree.phy")
12 |
13 | 2) [primate\_spec.txt](data_files/ch2/primate_spec.txt "primate_spec.txt")
14 |
15 | 3) [bird\_trees.tre](data_files/ch2/bird_trees.tre "bird_trees.tre")
16 |
17 | ← [back to the list of OPMs](README.md "Practice")
18 |
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2 |
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1 | Figures for Chapter 11.
2 |
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1 | Figures for Chapter 2.
2 |
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1 | Figures for Chapter 4.
2 |
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1 | Figures for Chapter 5.
2 |
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1 | Figures for Chapter 6.
2 |
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1 | Figures for Chapter 7.
2 |
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1 | Figures for Chapter 8.
2 |
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/online_practical_material/data_files/ch10/Primates.txt:
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1 | Cercocebus_torquatus 1 1
2 | Cercopithecus_aethiops 0 1
3 | Cercopithecus_mona 0 0
4 | Cercopithecus_nictitans 0 0
5 | Colobus_angolensis 0 1
6 | Colobus_guereza 0 0
7 | Colobus_polykomos 0 1
8 | Gorilla_gorilla 0 0
9 | Homo_sapiens 0 0
10 | Hylobates_agilis 0 0
11 | Hylobates_concolor 0 0
12 | Hylobates_gabriellae 0 0
13 | Hylobates_hoolock 0 0
14 | Hylobates_klossii 0 0
15 | Hylobates_lar 0 0
16 | Hylobates_leucogenys 0 0
17 | Hylobates_moloch 0 0
18 | Hylobates_muelleri 0 0
19 | Hylobates_pileatus 0 0
20 | Hylobates_syndactylus 0 0
21 | Macaca_brunnescens 1 1
22 | Macaca_cyclopis - 1
23 | Macaca_fascicularis - 1
24 | Macaca_hecki 1 1
25 | Macaca_maura 1 1
26 | Macaca_mulatta - 1
27 | Macaca_nemestrina 1 1
28 | Macaca_nigra 1 1
29 | Macaca_nigriscens 1 1
30 | Macaca_ochreata 1 1
31 | Macaca_silenus 1 1
32 | Macaca_sylvanus 1 1
33 | Macaca_tonkeana 1 1
34 | Mandrillus_leucophaeus 1 1
35 | Mandrillus_sphinx 1 1
36 | asalis_larvatus 0 0
37 | Pan_paniscus 1 1
38 | Pan_troglodytes 1 1
39 | Papio_anubis 1 1
40 | Papio_cynocephalus 1 1
41 | Papio_hamadryas 1 1
42 | Pongo_pygmaeus 0 0
43 | Pongo_pygmaeus_abelii 0 0
44 | Presbytis_francoisi 0 0
45 | Presbytis_phayrei 0 0
46 | Presbytis_senex 0 0
47 | Procolobus_badius 1 1
48 | Pygathrix_nemaeus 0 1
49 | Pygathrix_roxellana 0 1
50 | Rhinopithecus_avunculus 0 1
51 | Rhinopithecus_bieti 0 1
52 | Semnopithecus_entellus 0 1
53 | Trachypithecus_cristatus 0 0
54 | Trachypithecus_francoisi 0 0
55 | Trachypithecus_geei 0 0
56 | Trachypithecus_johnii 0 0
57 | Trachypithecus_phayrei 0 -
58 | Trachypithecus_pileatus 0 0
59 | Trachypithecus_vetulus 0 0
60 | Macaca_Arctoides 0 1
61 |
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/online_practical_material/data_files/ch10/ch10_data.md:
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1 | Data files for Chapter 10.
2 |
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/online_practical_material/data_files/ch11/ch11_data.md:
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1 | Data files for Chapter 11.
2 |
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/online_practical_material/data_files/ch19/tables.pdf:
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/online_practical_material/data_files/ch2/ch2_data.md:
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1 | Data files for Chapter 2.
2 |
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/online_practical_material/data_files/ch4/Centrarchidae.tre:
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1 | (Acantharchus_pomotis:0.3119231913,(((((Lepomis_gibbosus:0.07280374575,(Lepomis_microlophus:0.03213022453,(Lepomis_punctatus:0.01550794074,Lepomis_miniatus:0.01550794074):0.01662228379):0.04067352122):0.01829379836,(Lepomis_auritus:0.03890914473,(Lepomis_marginatus:0.0252584424,Lepomis_megalotis:0.0252584424):0.01365070233):0.05218839937):0.04485230765,((Lepomis_humilis:0.04800961295,Lepomis_macrochirus:0.04800961295):0.07373236495,(Lepomis_gulosus:0.06128886759,(Lepomis_symmetricus:0.02405123743,Lepomis_cyanellus:0.02405123743):0.03723763016):0.06045311031):0.01420787385):0.09444057324,((Micropterus_cataractae:0.05989593878,(Micropterus_coosae:0.05506711891,(Micropterus_notius:0.0473595795,(Micropterus_treculi:0.03816624936,(Micropterus_salmoides:0.02637278545,Micropterus_floridanus:0.02637278545):0.01179346391):0.009193330139):0.007707539409):0.004828819871):0.01810807452,(Micropterus_punctulatus:0.01550794074,Micropterus_dolomieu:0.01550794074):0.06249607256):0.1523864117):0.03835197321,(Centrarchus_macropterus:0.2120037647,((Enneacanthus_chaetodon:0.1051196941,(Enneacanthus_gloriosus:0.037423354,Enneacanthus_obesus:0.037423354):0.06769634011):0.09546205437,((Pomoxis_annularis:0.1114343047,Pomoxis_nigromaculatus:0.1114343047):0.06667485899,(Archoplites_interruptus:0.1439359769,((Ambloplites_ariommus:0.02720854273,Ambloplites_rupestris:0.02720854273):0.05488139507,(Ambloplites_cavifrons:0.06816064972,Ambloplites_constellatus:0.06816064972):0.01392928809):0.06184603912):0.03417318678):0.02247258478):0.01142201623):0.05673863348):0.04318079308);
2 |
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/online_practical_material/data_files/ch4/ch4_data.md:
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1 | Data files for Chapter 4.
2 |
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/online_practical_material/data_files/ch5/ch5_data.md:
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1 | Data files for Chapter 5.
2 |
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/online_practical_material/data_files/ch6/ch6_data.md:
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1 | Data files for Chapter 6.
2 |
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/online_practical_material/data_files/ch7/ch7_data.md:
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1 | Data files for Chapter 7.
2 |
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/online_practical_material/data_files/ch8/ch8_data.md:
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1 | Data files for Chapter 8.
2 |
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/online_practical_material/data_files/ch8/storks.csv:
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1 | Country,Area,Storks,Humans,Birth
2 | Albania,28750,100,3.2,83
Austria,83860,300,7.6,87
Belgium,30520,1,9.9,118
Bulgaria,111000,5000,9.0,117
Denmark,43100,9,5.1,59
France,544000,140,56,774
Germany,357000,3300,78,901
Greece,132000,2500,10,106
Holland,41900,4,15,188
Hungary,93000,5000,11,124
Italy,301280,5,57,551
Poland,312680,30000,38,610
Portugal,92390,1500,10,120
Romania,237500,5000,23,367
Spain,504750,8000,39,439
Switzerland,41290,150,6.7,82
Turkey,779450,25000,56,1576
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/online_practical_material/exercises_and_tutorials/chapter-10-keeping-updated-bayesian-approaches-phylogenetic-comparative-methods-focus-markov-chain-models-discrete-character-evolution.md:
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1 | ---
2 | title: "Chapter 10 – Keeping Yourself Updated: Bayesian Approaches in Phylogenetic Comparative Methods with a Focus on Markov Chain Models of Discrete Character Evolution"
3 | date: "2014-11-30"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 10 – Keeping Yourself Updated: Bayesian Approaches in Phylogenetic Comparative Methods with a Focus on Markov Chain Models of Discrete Character Evolution
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [Using BayesTraits for performing phylogenetic comparative analyses based on Bayesian approaches](http://www.mpcm-evolution.com/OPM/Chapter10_OPM/OPM_chap10.pdf "OPM_chap10.pdf")
13 |
14 | ### Sources and example data (you need to download them to execute the materials above)
15 |
16 | 1) [primates.txt](http://www.mpcm-evolution.com/OPM/Chapter10_OPM/Primates.txt "Primates.txt")
17 |
18 | 2) [primates.trees](http://www.mpcm-evolution.com/OPM/Chapter10_OPM/Primates.trees "primates.trees")
19 |
20 |
21 |
22 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
23 |
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/online_practical_material/exercises_and_tutorials/chapter-11-1-simple-model-mcmcglmm.md:
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1 | ---
2 | title: "Chapter 11 – 1) A simple model in MCMCglmm"
3 | date: "2014-09-06"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 11 – General Quantitative Genetic Methods for Comparative Biology
9 |
10 | ### 1) A simple model in MCMCglmm
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter11\_OPM/1\_simple.html" width="100%" height="4500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 11 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-11 "Chapter 11 – General Quantitative Genetic Methods for Comparative Biology")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-11-2-multiple-measurements-model-mcmcglmm.md:
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1 | ---
2 | title: "Chapter 11 – 2) Multiple measurements model in MCMCglmm"
3 | date: "2014-09-06"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 11 – General Quantitative Genetic Methods for Comparative Biology
9 |
10 | ### 2) Multiple measurements model in MCMCglmm
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter11\_OPM/2\_multi.html" width="100%" height="2500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 11 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-11 "Chapter 11 – General Quantitative Genetic Methods for Comparative Biology")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-11-3-example-meta-analysis-fishers-transformation-r-zr.md:
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1 | ---
2 | title: "Chapter 11 – 3) An example of meta-analysis with Fisher's transformation of r (Zr)"
3 | date: "2014-09-06"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 11 – General Quantitative Genetic Methods for Comparative Biology
9 |
10 | ### 3) An example of meta-analysis with Fisher's transformation of r (Zr)
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter11\_OPM/3\_fisher.html" width="100%" height="2500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 11 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-11 "Chapter 11 – General Quantitative Genetic Methods for Comparative Biology")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-11-4-example-non-gaussian-trait-using-count-data.md:
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1 | ---
2 | title: "Chapter 11 – 4) An example of non-Gaussian trait using count data"
3 | date: "2014-09-06"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 11 – General Quantitative Genetic Methods for Comparative Biology
9 |
10 | ### 4) An example of non-Gaussian trait using count data
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter11\_OPM/4\_nongaussian.html" width="100%" height="1800" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 11 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-11 "Chapter 11 – General Quantitative Genetic Methods for Comparative Biology")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-11-bibliography.md:
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1 | ---
2 | title: "Chapter 11 – Bibliography"
3 | date: "2014-09-06"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 11 – General Quantitative Genetic Methods for Comparative Biology
9 |
10 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter11\_OPM/biblio.html" width="100%" height="800" scrolling="yes"\]
11 |
12 | ← [back to the list of Chapter 11 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-11 "Chapter 11 – General Quantitative Genetic Methods for Comparative Biology")
13 |
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/online_practical_material/exercises_and_tutorials/chapter-11-example-mar-comparative-data.md:
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1 | ---
2 | title: "Chapter 11 – 5) An example with MAR comparative data"
3 | date: "2014-09-06"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 11 – General Quantitative Genetic Methods for Comparative Biology
9 |
10 | ### 5) An example with MAR comparative data
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter11\_OPM/5\_missing.html" width="100%" height="1900" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 11 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-11 "Chapter 11 – General Quantitative Genetic Methods for Comparative Biology")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-12-1-evolutionary-models-different-combinations-predictors.md:
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1 | ---
2 | title: "Chapter 12: 1 Evolutionary models with different combinations of predictors"
3 | date: "2014-10-03"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 12 – Multimodel-Inference in Comparative Analyses
9 |
10 | ### 1) Evolutionary models with different combinations of predictors
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter12\_OPM/1\_multi\_predictors\_OUT\_corr.html" width="100%" height="7200" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 12 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-21/chapter-21-1-exercises-analyses-displaying-results "Chapter 21: 1 Exercises (analyses and displaying results)")
15 |
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1 | ---
2 | title: "Chapter 12: 2 Dealing with phylogenetic uncertainty: inference across models considering different phylogenetic hypotheses"
3 | date: "2014-10-03"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 12 – Multimodel-Inference in Comparative Analyses
9 |
10 | ### 2) Dealing with phylogenetic uncertainty: inference across models considering different phylogenetic hypotheses
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter12\_OPM/2\_phylo\_uncertainity\_OUT.html" width="100%" height="10500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 12 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-21/chapter-21-1-exercises-analyses-displaying-results "Chapter 21: 1 Exercises (analyses and displaying results)")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-12-3-playing-statistical-weights-adjusting-omega-parameter.md:
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1 | ---
2 | title: "Chapter 12: 3 Playing with statistical weights (adjusting the “omega” parameter)"
3 | date: "2014-10-03"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 12 – Multimodel-Inference in Comparative Analyses
9 |
10 | ### 3) Playing with statistical weights (adjusting the “omega” parameter)
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter12\_OPM/3\_weights\_OUT.html" width="100%" height="10500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 12 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-21/chapter-21-1-exercises-analyses-displaying-results "Chapter 21: 1 Exercises (analyses and displaying results)")
15 |
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1 | ---
2 | title: "Chapter 12: 4 Multimodel inference when exploring multidimensional parameter space (simultaneously varying lambda and omega)"
3 | date: "2014-10-03"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 12 – Multimodel-Inference in Comparative Analyses
9 |
10 | ### 4) Multimodel inference when exploring multidimensional parameter space (simultaneously varying lambda and omega)
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter12\_OPM/4\_weight&lambda\_OUT.html" width="100%" height="10500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 12 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-21/chapter-21-1-exercises-analyses-displaying-results "Chapter 21: 1 Exercises (analyses and displaying results)")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-13-1-trees.md:
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1 | ---
2 | title: "Chapter 13 – 1) Trees"
3 | date: "2014-09-08"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 13 – Simulation of Phylogenetic Data
9 |
10 | ### 1) Trees
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter13\_OPM/1\_Trees.html" width="100%" height="2500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 13 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-13 "Chapter 13 – Simulation of Phylogenetic Data")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-13-2-traits.md:
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1 | ---
2 | title: "Chapter 13 – 2) Traits"
3 | date: "2014-09-08"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 13 – Simulation of Phylogenetic Data
9 |
10 | ### 2) Traits
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter13\_OPM/2\_Traits.html" width="100%" height="7800" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 13 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-13 "Chapter 13 – Simulation of Phylogenetic Data")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-13-3-trees-traits.md:
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1 | ---
2 | title: "Chapter 13 – 3) Trees and traits"
3 | date: "2014-09-08"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 13 – Simulation of Phylogenetic Data
9 |
10 | ### 3) Trees and traits
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter13\_OPM/3\_Trees\_and\_traits.html" width="100%" height="900" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 13 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-13 "Chapter 13 – Simulation of Phylogenetic Data")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-17-1-brief-description-program-code.md:
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1 | ---
2 | title: "Chapter 17: 1 A brief description of the program code"
3 | date: "2014-11-07"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 17 – Detecting Phenotypic Selection by Approximate Bayesian Computation in Phylogenetic Comparative Methods
9 |
10 | ### 1) A brief description of the program code
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter17\_OPM/html\_frame\_chap17.html" width="100%" height="3000" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 17 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-17 "Chapter 17 – Detecting Phenotypic Selection by Approximate Bayesian Computation in Phylogenetic Comparative Methods")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-19-1-calculating-community-phylogenetic-metrics-opm.md:
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1 | ---
2 | title: "Chapter 19: 1 Calculating community phylogenetic metrics OPM"
3 | date: "2014-09-01"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 19 – Metrics and Models of Community Phylogenetics
9 |
10 | ### 1) Calculating community phylogenetic metrics
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter19\_OPM/1\_Calculating\_community\_phylogenetic\_metrics\_OPM.html" width="100%" height="2000" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 19 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-19 "Chapter 19 – Metrics and Models of Community Phylogenetics")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-21-1-exercises-analyses-displaying-results.md:
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1 | ---
2 | title: "Chapter 21: 1 Exercises (analyses and displaying results)"
3 | date: "2014-09-27"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 21 – Phylogenetic Prediction to Identify “Evolutionary Singularities"
9 |
10 | ### 1) Exercises (analyses and displaying results)
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter21\_OPM/html\_frame\_chap21.html" width="100%" height="6000" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 21 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-21 "Chapter 21 – Phylogenetic Prediction to Identify “Evolutionary Singularities”")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-22-1-example-time-scaling-using-r-package-paleotree.md:
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1 | ---
2 | title: "Chapter 22: 1 An example of time-scaling using the R package “paleotree\""
3 | date: "2014-10-18"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 22 – Preparing Paleontological Datasets for Phylogenetic Comparative Methods
9 |
10 | ### 1) An example of time-scaling using the R package “paleotree"
11 |
12 | \[iframe src="http://mpcm-evolution.com/OPM/Chapter22\_OPM/html\_frame\_chap22\_OUT.html" width="100%" height="7500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 22 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-22 "Chapter 22 – Preparing Paleontological Datasets for Phylogenetic Comparative Methods")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-4-1-codes-used-produce-twelve-figures-chapter.md:
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1 | ---
2 | title: "Chapter 4: 1 Codes that were used to produce the twelve figures in the chapter"
3 | date: "2014-11-30"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 4 – Graphical Methods for Visualizing Comparative Data on Phylogenies
9 |
10 | ### 1) Codes that were used to produce the twelve figures in the chapter
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter4\_OPM/Revell\_Chapter4\_OPM\_mod1.html" width="100%" height="20500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 4 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-4 "Chapter 4 – Graphical Methods for Visualizing Comparative Data on Phylogenies")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-6-1exercises-testing-assumptions-statistical-issues-framework-phylogenetic-generalized-least-squares.md:
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1 | ---
2 | title: "Chapter 6: 1Exercises for testing assumptions and other statistical issues in the framework of Phylogenetic Generalized Least Squares"
3 | date: "2014-11-10"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 6 – Statistical Issues and Assumptions of Phylogenetic Generalized Least Squares
9 |
10 | ### 1) Exercises for testing assumptions and other statistical issues in the framework of Phylogenetic Generalized Least Squares
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter6\_OPM/html\_frame\_chap6.html" width="100%" height="22100" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 6 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-6 "Chapter 6 – Statistical Issues and Assumptions of Phylogenetic Generalized Least Squares")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-7-1-repeatability-opm.md:
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1 | ---
2 | title: "Chapter 7: 1 Repeatability OPM"
3 | date: "2014-08-20"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 7 - Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights
9 |
10 | ### 1) Repeatability
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter7\_OPM/1\_repeatability\_OPM.html" width="100%" height="2500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 7 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-7 "Chapter 7 – Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-7-2-data-opm.md:
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1 | ---
2 | title: "Chapter 7: 2 Data PreparationOPM"
3 | date: "2014-08-20"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 7 - Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights
9 |
10 | ### 2) Data Preparation
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter7\_OPM/2\_data\_OPM.html" width="100%" height="2500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 7 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-7 "Chapter 7 – Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-7-3-weighted-regr-opm.md:
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1 | ---
2 | title: "Chapter 7: 3 weighted regr OPM"
3 | date: "2014-08-20"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 7 - Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights
9 |
10 | ### 3) Weighted regression
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter7\_OPM/3\_weighted\_regr\_OPM.html" width="100%" height="2700" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 7 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-7 "Chapter 7 – Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-7-4-univariate-opm.md:
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1 | ---
2 | title: "Chapter 7: 4 univariate OPM"
3 | date: "2014-08-20"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 7 - Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights
9 |
10 | ### 4) Fitting univariate evolutionary models with intraspecific varaince to estimate species-specific traits (means and variances), ancestral states, evolutionary rate and phylogenetic signal
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter7\_OPM/4\_univariate\_OPM.html" width="100%" height="4500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 7 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-7 "Chapter 7 – Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-7-5-bivariate-opm.md:
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1 | ---
2 | title: "Chapter 7: 5 bivariate OPM"
3 | date: "2014-08-20"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 7 - Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights
9 |
10 | ### 5) Studying correlated evolution in multivariate phylogenetic regression models by incorporating within-species variance
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter7\_OPM/5\_bivariate\_OPM.html" width="100%" height="10200" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 7 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-7 "Chapter 7 – Uncertainties Due to Within-Species Variation in Comparative Studies: Measurement Errors and Statistical Weights")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-8-1-baby-delivering-storks-example.md:
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1 | ---
2 | title: "Chapter 8: 1 The baby-delivering storks example"
3 | date: "2014-09-27"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 8 – An Introduction to Phylogenetic Path Analysis
9 |
10 | ### 1) The baby-delivering storks example
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter8\_OPM/Storks example.html" width="100%" height="5200" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 8 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-8 "Chapter 8 – An Introduction to Phylogenetic Path Analysis")
15 |
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/online_practical_material/exercises_and_tutorials/chapter-8-2-step-step-guide-phylogenetic-path-analysis-using-d-sep-method-rhinograds-example.md:
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1 | ---
2 | title: "Chapter 8: 2 A step-by-step guide to phylogenetic path analysis using the d-sep method (Rhinograds example)"
3 | date: "2014-09-27"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 8 – An Introduction to Phylogenetic Path Analysis
9 |
10 | ### 1) A step-by-step guide to phylogenetic path analysis using the d-sep method (Rhinograds example)
11 |
12 | \[iframe src="https://mpcm-evolution.com/OPM/Chapter8\_OPM/Rhinograds example.html" width="100%" height="10500" scrolling="yes"\]
13 |
14 | ← [back to the list of Chapter 8 OPMs](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-8 "Chapter 8 – An Introduction to Phylogenetic Path Analysis")
15 |
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1 | Cercocebus_torquatus 1 1
2 | Cercopithecus_aethiops 0 1
3 | Cercopithecus_mona 0 0
4 | Cercopithecus_nictitans 0 0
5 | Colobus_angolensis 0 1
6 | Colobus_guereza 0 0
7 | Colobus_polykomos 0 1
8 | Gorilla_gorilla 0 0
9 | Homo_sapiens 0 0
10 | Hylobates_agilis 0 0
11 | Hylobates_concolor 0 0
12 | Hylobates_gabriellae 0 0
13 | Hylobates_hoolock 0 0
14 | Hylobates_klossii 0 0
15 | Hylobates_lar 0 0
16 | Hylobates_leucogenys 0 0
17 | Hylobates_moloch 0 0
18 | Hylobates_muelleri 0 0
19 | Hylobates_pileatus 0 0
20 | Hylobates_syndactylus 0 0
21 | Macaca_brunnescens 1 1
22 | Macaca_cyclopis - 1
23 | Macaca_fascicularis - 1
24 | Macaca_hecki 1 1
25 | Macaca_maura 1 1
26 | Macaca_mulatta - 1
27 | Macaca_nemestrina 1 1
28 | Macaca_nigra 1 1
29 | Macaca_nigriscens 1 1
30 | Macaca_ochreata 1 1
31 | Macaca_silenus 1 1
32 | Macaca_sylvanus 1 1
33 | Macaca_tonkeana 1 1
34 | Mandrillus_leucophaeus 1 1
35 | Mandrillus_sphinx 1 1
36 | asalis_larvatus 0 0
37 | Pan_paniscus 1 1
38 | Pan_troglodytes 1 1
39 | Papio_anubis 1 1
40 | Papio_cynocephalus 1 1
41 | Papio_hamadryas 1 1
42 | Pongo_pygmaeus 0 0
43 | Pongo_pygmaeus_abelii 0 0
44 | Presbytis_francoisi 0 0
45 | Presbytis_phayrei 0 0
46 | Presbytis_senex 0 0
47 | Procolobus_badius 1 1
48 | Pygathrix_nemaeus 0 1
49 | Pygathrix_roxellana 0 1
50 | Rhinopithecus_avunculus 0 1
51 | Rhinopithecus_bieti 0 1
52 | Semnopithecus_entellus 0 1
53 | Trachypithecus_cristatus 0 0
54 | Trachypithecus_francoisi 0 0
55 | Trachypithecus_geei 0 0
56 | Trachypithecus_johnii 0 0
57 | Trachypithecus_phayrei 0 -
58 | Trachypithecus_pileatus 0 0
59 | Trachypithecus_vetulus 0 0
60 | Macaca_Arctoides 0 1
61 |
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1 | (Acantharchus_pomotis:0.3119231913,(((((Lepomis_gibbosus:0.07280374575,(Lepomis_microlophus:0.03213022453,(Lepomis_punctatus:0.01550794074,Lepomis_miniatus:0.01550794074):0.01662228379):0.04067352122):0.01829379836,(Lepomis_auritus:0.03890914473,(Lepomis_marginatus:0.0252584424,Lepomis_megalotis:0.0252584424):0.01365070233):0.05218839937):0.04485230765,((Lepomis_humilis:0.04800961295,Lepomis_macrochirus:0.04800961295):0.07373236495,(Lepomis_gulosus:0.06128886759,(Lepomis_symmetricus:0.02405123743,Lepomis_cyanellus:0.02405123743):0.03723763016):0.06045311031):0.01420787385):0.09444057324,((Micropterus_cataractae:0.05989593878,(Micropterus_coosae:0.05506711891,(Micropterus_notius:0.0473595795,(Micropterus_treculi:0.03816624936,(Micropterus_salmoides:0.02637278545,Micropterus_floridanus:0.02637278545):0.01179346391):0.009193330139):0.007707539409):0.004828819871):0.01810807452,(Micropterus_punctulatus:0.01550794074,Micropterus_dolomieu:0.01550794074):0.06249607256):0.1523864117):0.03835197321,(Centrarchus_macropterus:0.2120037647,((Enneacanthus_chaetodon:0.1051196941,(Enneacanthus_gloriosus:0.037423354,Enneacanthus_obesus:0.037423354):0.06769634011):0.09546205437,((Pomoxis_annularis:0.1114343047,Pomoxis_nigromaculatus:0.1114343047):0.06667485899,(Archoplites_interruptus:0.1439359769,((Ambloplites_ariommus:0.02720854273,Ambloplites_rupestris:0.02720854273):0.05488139507,(Ambloplites_cavifrons:0.06816064972,Ambloplites_constellatus:0.06816064972):0.01392928809):0.06184603912):0.03417318678):0.02247258478):0.01142201623):0.05673863348):0.04318079308);
2 |
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/online_practical_material/iframe/Chapter8_OPM/download/storks.csv:
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1 | Country,Area,Storks,Humans,Birth
2 | Albania,28750,100,3.2,83
Austria,83860,300,7.6,87
Belgium,30520,1,9.9,118
Bulgaria,111000,5000,9.0,117
Denmark,43100,9,5.1,59
France,544000,140,56,774
Germany,357000,3300,78,901
Greece,132000,2500,10,106
Holland,41900,4,15,188
Hungary,93000,5000,11,124
Italy,301280,5,57,551
Poland,312680,30000,38,610
Portugal,92390,1500,10,120
Romania,237500,5000,23,367
Spain,504750,8000,39,439
Switzerland,41290,150,6.7,82
Turkey,779450,25000,56,1576
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/online_practical_material/online-practical-material-chapter-13.md:
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1 | ---
2 | title: "Chapter 13 – Simulation of Phylogenetic Data"
3 | date: "2014-09-08"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 13 – Simulation of Phylogenetic Data
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [Trees](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-13/chapter-13-1-trees "Chapter 13 – 1) Trees")
13 |
14 | 2) [Traits](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-13/chapter-13-2-traits "Chapter 13 – 2) Traits")
15 |
16 | 3) [Trees and traits](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-13/chapter-13-3-trees-traits "Chapter 13 – 3) Trees and traits")
17 |
18 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
19 |
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/online_practical_material/online-practical-material-chapter-17.md:
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1 | ---
2 | title: "Chapter 17 – Detecting Phenotypic Selection by Approximate Bayesian Computation in Phylogenetic Comparative Methods"
3 | date: "2014-11-07"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 17 – Detecting Phenotypic Selection by Approximate Bayesian Computation in Phylogenetic Comparative Methods
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [A brief description of the program code](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-17/chapter-17-1-brief-description-program-code "Chapter 17: 1 A brief description of the program code")
13 |
14 | ### Sources and example data (you need to download them to execute the materials above)
15 |
16 | 1) [ABC\_PCM.c](http://www.mpcm-evolution.com/OPM/Chapter17_OPM/download/ABC_PCM.c "ABC_PCM.c")
17 |
18 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
19 |
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/online_practical_material/online-practical-material-chapter-19.md:
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1 | ---
2 | title: "Chapter 19 – Metrics and Models of Community Phylogenetics"
3 | date: "2014-09-01"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 19 – Metrics and Models of Community Phylogenetics
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [Calculating community phylogenetic metrics](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-19/chapter-19-1-calculating-community-phylogenetic-metrics-opm "Chapter 19: 1 Calculating community phylogenetic metrics OPM")
13 |
14 | ### Sources and example data (you need to download them to execute the materials above)
15 |
16 | 1) [metrics.R](http://www.mpcm-evolution.com/OPM/Chapter19_OPM/download/metrics.R "metrics.R")
17 |
18 | 2) [functions.R](http://www.mpcm-evolution.com/OPM/Chapter19_OPM/download/functions.R "functions.R")
19 |
20 | 3) [figures.R](http://www.mpcm-evolution.com/OPM/Chapter19_OPM/download/figures.R "figures.R")
21 |
22 | 4) [pglmm.R](http://www.mpcm-evolution.com/OPM/Chapter19_OPM/download/pglmm.R "pglmm.R")
23 |
24 | 5) [tables.pdf](http://www.mpcm-evolution.com/OPM/Chapter19_OPM/download/tables.pdf "tables.pdf")
25 |
26 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
27 |
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/online_practical_material/online-practical-material-chapter-21.md:
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1 | ---
2 | title: "Chapter 21 – Phylogenetic Prediction to Identify “Evolutionary Singularities\""
3 | date: "2014-09-27"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 21 – Phylogenetic Prediction to Identify “Evolutionary Singularities"
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [Exercises (analyses and displaying results)](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-21/chapter-21-1-exercises-analyses-displaying-results "Chapter 21: 1 Exercises (analyses and displaying results)")
13 |
14 | ### Sources and example data (you need to download them to execute the materials above)
15 |
16 | 1) [e.dataIMI\_corrected.csv](http://mpcm-evolution.com/OPM/Chapter21_OPM/download/e.dataIMI_corrected.csv "e.dataIMI_corrected.csv")
17 |
18 | 2) [e.IMI.TreeBlock\_10kTrees\_Primates\_Version3.nex](http://mpcm-evolution.com/OPM/Chapter21_OPM/download/e.IMI.TreeBlock_10kTrees_Primates_Version3.nex.txt "e.IMI.TreeBlock_10kTrees_Primates_Version3.nex")
19 |
20 | 3) [BayesModelS\_v22.R](http://mpcm-evolution.com/OPM/Chapter21_OPM/download/BayesModelS_v22.R "BayesModelS_v22.R")
21 |
22 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
23 |
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/online_practical_material/online-practical-material-chapter-22.md:
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1 | ---
2 | title: "Chapter 22 – Preparing Paleontological Datasets for Phylogenetic Comparative Methods"
3 | date: "2014-10-18"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 22 – Preparing Paleontological Datasets for Phylogenetic Comparative Methods
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [An example of time-scaling using the R package “paleotree"](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-22/chapter-22-1-example-time-scaling-using-r-package-paleotree "Chapter 22: 1 An example of time-scaling using the R package “paleotree”")
13 |
14 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
15 |
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/online_practical_material/online-practical-material-chapter-4.md:
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1 | ---
2 | title: "Chapter 4 – Graphical Methods for Visualizing Comparative Data on Phylogenies"
3 | date: "2014-11-30"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 4 – Graphical Methods for Visualizing Comparative Data on Phylogenies
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [Codes that were used to produce the twelve figures in the chapter](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-4/chapter-4-1-codes-used-produce-twelve-figures-chapter "Chapter 4: 1 Codes that were used to produce the twelve figures in the chapter")
13 |
14 | ### Sources and example data (you need to download them to execute the materials above)
15 |
16 | 1) [Centrarchidae.tre](http://www.mpcm-evolution.com/OPM/Chapter4_OPM/Centrarchidae.tre "Centrarchidae.tre")
17 |
18 | 2) [elopomorph.tre](http://www.mpcm-evolution.com/OPM/Chapter4_OPM/elopomorph.tre "elopomorph.tre")
19 |
20 | 3) [elopomorph.csv](http://www.mpcm-evolution.com/OPM/Chapter4_OPM/elopomorph.csv "elophomorph.csv")
21 |
22 | 4) [anole.data.csv](http://www.mpcm-evolution.com/OPM/Chapter4_OPM/anole.data.csv "anole.data.csv")
23 |
24 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
25 |
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/online_practical_material/online-practical-material-chapter-5.md:
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1 | ---
2 | title: "Chapter 5 – A Primer on Phylogenetic Generalised Least Squares"
3 | date: "2014-11-07"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 5 – A Primer on Phylogenetic Generalised Least Squares
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [Phylogenetic Generalized Least Squares in R](http://www.mpcm-evolution.com/OPM/Chapter5_OPM/OPM_chap5.pdf "OPM_chap5.pdf") (pdf file)
13 |
14 | ### Sources and example data (you need to download them to execute the materials above)
15 |
16 | 1) [vcv2phylo.R](http://mpcm-evolution.com/OPM/Chapter5_OPM/download/vcv2phylo.R "vcv2phylo.R")
17 |
18 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
19 |
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/online_practical_material/online-practical-material-chapter-6.md:
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1 | ---
2 | title: "Chapter 6 – Statistical Issues and Assumptions of Phylogenetic Generalized Least Squares"
3 | date: "2014-11-10"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 6 – Statistical Issues and Assumptions of Phylogenetic Generalized Least Squares
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [Exercises for testing assumptions and other statistical issues in the framework of Phylogenetic Generalized Least Squares](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-6/chapter-6-1exercises-testing-assumptions-statistical-issues-framework-phylogenetic-generalized-least-squares "Chapter 6: 1Exercises for testing assumptions and other statistical issues in the framework of Phylogenetic Generalized Least Squares")
13 |
14 | ### Sources and example data (you need to download them to execute the materials above)
15 |
16 | 1) [fict\_phylo.nex](http://mpcm-evolution.com/OPM/Chapter6_OPM/download/fict_phylo.nex "fict_phylo.nex")
17 |
18 | 2) [covariates.txt](http://mpcm-evolution.com/OPM/Chapter6_OPM/download/covariates.txt "covariates.txt")
19 |
20 | 3) [pgls\_check\_fncs.r](http://mpcm-evolution.com/OPM/Chapter6_OPM/download/pgls_check_fncs.r "pgls_check_fncs.r")
21 |
22 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
23 |
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/online_practical_material/online-practical-material-chapter-8.md:
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1 | ---
2 | title: "Chapter 8 – An Introduction to Phylogenetic Path Analysis"
3 | date: "2014-09-27"
4 | ---
5 |
6 | # **Online Practical Materials**
7 |
8 | ## Chapter 8 – An Introduction to Phylogenetic Path Analysis
9 |
10 | ### Exercises and tutorials
11 |
12 | 1) [The baby-delivering storks example](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-8/chapter-8-1-baby-delivering-storks-example "Chapter 8: 1 The baby-delivering storks example")
13 |
14 | 2) [A step-by-step guide to phylogenetic path analysis using the d-sep method (Rhinograds example)](http://www.mpcm-evolution.com/practice/online-practical-material-chapter-8/chapter-8-2-step-step-guide-phylogenetic-path-analysis-using-d-sep-method-rhinograds-example "Chapter 8: 2 A step-by-step guide to phylogenetic path analysis using the d-sep method (Rhinograds example)")
15 |
16 | ### Sources and example data (you need to download them to execute the materials above)
17 |
18 | 1) [storks.csv](http://mpcm-evolution.com/OPM/Chapter8_OPM/download/storks.csv "storks.csv")
19 |
20 | 2) [rhino.csv](http://mpcm-evolution.com/OPM/Chapter8_OPM/download/rhino.csv "rhino.csv")
21 |
22 | 3) [rhino.tree](http://mpcm-evolution.com/OPM/Chapter8_OPM/download/rhino.tree "rhino.tree")
23 |
24 | ← [back to the list of OPMs](http://www.mpcm-evolution.com/practice "Practice")
25 |
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