phytools: an R package for phylogenetic comparative biology (and other things)
TL;DR: A new, multifunctional phylogenetics package, phytools, for the R statistical computing environment is presented, with a focus on phylogenetic tree-building in 2.1.
Abstract: Summary
1. Here, I present a new, multifunctional phylogenetics package, phytools, for the R statistical computing environment.
2. The focus of the package is on methods for phylogenetic comparative biology; however, it also includes tools for tree inference, phylogeny input/output, plotting, manipulation and several other tasks.
3. I describe and tabulate the major methods implemented in phytools, and in addition provide some demonstration of its use in the form of two illustrative examples.
4. Finally, I conclude by briefly describing an active web-log that I use to document present and future developments for phytools. I also note other web resources for phylogenetics in the R computational environment.
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TL;DR: An r package, ggtree, which provides programmable visualization and annotation of phylogenetic trees, which can read more tree file formats than other softwares, and support visualization of phylo, multiphylo, phylo4, phyla4d, obkdata and phyloseq tree objects defined in other r packages.
Abstract: Summary
We present an r package, ggtree, which provides programmable visualization and annotation of phylogenetic trees.
ggtree can read more tree file formats than other softwares, including newick, nexus, NHX, phylip and jplace formats, and support visualization of phylo, multiphylo, phylo4, phylo4d, obkdata and phyloseq tree objects defined in other r packages. It can also extract the tree/branch/node-specific and other data from the analysis outputs of beast, epa, hyphy, paml, phylodog, pplacer, r8s, raxml and revbayes software, and allows using these data to annotate the tree.
The package allows colouring and annotation of a tree by numerical/categorical node attributes, manipulating a tree by rotating, collapsing and zooming out clades, highlighting user selected clades or operational taxonomic units and exploration of a large tree by zooming into a selected portion.
A two-dimensional tree can be drawn by scaling the tree width based on an attribute of the nodes. A tree can be annotated with an associated numerical matrix (as a heat map), multiple sequence alignment, subplots or silhouette images.
The package ggtree is released under the artistic-2.0 license. The source code and documents are freely available through bioconductor (http://www.bioconductor.org/packages/ggtree).
2,692 citations
Cites methods from "phytools: an R package for phylogen..."
...Some packages, including APE (Paradis, Claude & Strimmer 2004) and PHYTOOLS (Revell 2012), which are capable of displaying and annotating trees, are developed using the base graphics system of R. OUTBREAKTOOLS (Jombart et al. 2014) and PHYLOSEQ (McMurdie & Holmes 2013) extended GGPLOT2 to draw phylogenetic trees....
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...Some packages, including APE (Paradis, Claude & Strimmer 2004) and PHYTOOLS (Revell 2012), which are capable of displaying and annotating trees, are developed using the base graphics system of R. OUTBREAKTOOLS (Jombart et al. 2014) and PHYLOSEQ (McMurdie & Holmes 2013) extended GGPLOT2 to draw…...
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TL;DR: Correlation of microbiome features with host quality of life and depression identified specific taxa and microbial pathways in two independent, large population cohorts, identifying links between microbial neuroactive potential and depression.
Abstract: The relationship between gut microbial metabolism and mental health is one of the most intriguing and controversial topics in microbiome research. Bidirectional microbiota-gut-brain communication has mostly been explored in animal models, with human research lagging behind. Large-scale metagenomics studies could facilitate the translational process, but their interpretation is hampered by a lack of dedicated reference databases and tools to study the microbial neuroactive potential. Surveying a large microbiome population cohort (Flemish Gut Flora Project, n =1,054) with validation in independent data sets (n(total) =1,070), we studied how microbiome features correlate with host quality of life and depression. Butyrate-producing Faecalibacterium and Coprococcus bacteria were consistently associated with higher quality of life indicators. Together with Dialister, Coprococcus spp. were also depleted in depression, even after correcting for the confounding effects of antidepressants. Using a module-based analytical framework, we assembled a catalogue of neuroactive potential of sequenced gut prokaryotes. Gut-brain module analysis of faecal metagenomes identified the microbial synthesis potential of the dopamine metabolite 3,4-dihydroxyphenylacetic acid as correlating positively with mental quality of life and indicated a potential role of microbial gamma-aminobutyric acid production in depression. Our results provide population-scale evidence for microbiome links to mental health, while emphasizing confounder importance.
1,011 citations
Beijing Genomics Institute1, University of Copenhagen2, Royal Veterinary College3, Seoul National University4, University of Nebraska–Lincoln5, University of Porto6, University of South Carolina7, Montclair State University8, Uppsala University9, National University of Singapore10, University of California, Berkeley11, South China University of Technology12, Chinese Academy of Sciences13, Kunming Institute of Zoology14, Howard Hughes Medical Institute15, Aberystwyth University16, University of Kent17, University of California, Riverside18, Mississippi State University19, Austral University of Chile20, Swedish University of Agricultural Sciences21, China Agricultural University22, Cardiff University23, Copenhagen Zoo24, Louisiana State University25, Washington University in St. Louis26, Xi'an Jiaotong University27, University of California, Santa Cruz28, Nova Southeastern University Oceanographic Center29, Smithsonian Conservation Biology Institute30, National Museum of Natural History31, Natural History Museum32, University of California, San Francisco33, Harvard University34, University of Florida35, University of Edinburgh36, New Mexico State University37, Macau University of Science and Technology38, Curtin University39
TL;DR: This work explored bird macroevolution using full genomes from 48 avian species representing all major extant clades to reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.
Abstract: Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.
872 citations
Cites methods from "phytools: an R package for phylogen..."
...To compare the rearrangement rate between vocal-learners and non-vocal learners, we used the phylogenetic ANOVA function implemented in R “phytools” package (128), which controlled for phylogenetic relatedness....
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TL;DR: The known species repertoire of the collective human gut microbiota is substantially expanded with the discovery of 1,952 uncultured bacterial species that greatly improve classification of understudied African and South American samples.
Abstract: The composition of the human gut microbiota is linked to health and disease, but knowledge of individual microbial species is needed to decipher their biological roles. Despite extensive culturing and sequencing efforts, the complete bacterial repertoire of the human gut microbiota remains undefined. Here we identify 1,952 uncultured candidate bacterial species by reconstructing 92,143 metagenome-assembled genomes from 11,850 human gut microbiomes. These uncultured genomes substantially expand the known species repertoire of the collective human gut microbiota, with a 281% increase in phylogenetic diversity. Although the newly identified species are less prevalent in well-studied populations compared to reference isolate genomes, they improve classification of understudied African and South American samples by more than 200%. These candidate species encode hundreds of newly identified biosynthetic gene clusters and possess a distinctive functional capacity that might explain their elusive nature. Our work expands the known diversity of uncultured gut bacteria, which provides unprecedented resolution for taxonomic and functional characterization of the intestinal microbiota.
795 citations
TL;DR: Phylogenetic signal is the tendency of related species to resemble each other more than species drawn at random from the same tree and various indices have been proposed for quantifying it.
Abstract: 1.ePhylogenetic signal is the tendency of related species to resemble each other more than species drawn at random from the same tree. This pattern is of considerable interest in a range of ecological and evolutionary research areas, and various indices have been proposed for quantifying it. Unfortunately, these indices often lead to contrasting results, and guidelines for choosing the most appropriate index are lacking.
2.eHere, we compare the performance of four commonly used indices using simulated data. Data were generated with numerical simulations of trait evolution along phylogenetic trees under a variety of evolutionary models. We investigated the sensitivity of the approaches to the size of phylogenies, the resolution of tree structure and the availability of branch length information, examining both the response of the selected indices and the power of the associated statistical tests.
3.eWe found that under a Brownian motion (BM) model of trait evolution, Abouheifrs Cmean and Pagelrs l performed well and substantially better than Moranrs I and Blombergrs K. Pagelrs l provided a reliable effect size measure and performed better for discriminating between more complex models of trait evolution, but was computationally more demanding than Abouheifrs Cmean. Blombergrs K was most suitable to capture the effects of changing evolutionary rates in simulation experiments.
4.eInterestingly, sample size influenced not only the uncertainty but also the expected values of most indices, while polytomies and missing branch length information had only negligible impacts.
5.eWe propose guidelines for choosing among indices, depending on (a) their sensitivity to true underlying patterns of phylogenetic signal, (b) whether a test or a quantitative measure is required and (c) their sensitivities to different topologies of phylogenies.
6.eThese guidelines aim to better assess phylogenetic signal and distinguish it from random trait distributions. They were developed under the assumption of BM, and additional simulations with more complex trait evolution models show that they are to a certain degree generalizable. They are particularly useful in comparative analyses, when requiring a proxy for niche similarity, and in conservation studies that explore phylogenetic loss associated with extinction risks of specific clades.
744 citations
Cites methods from "phytools: an R package for phylogen..."
...An alternative way would have been to compute the likelihoods with the functions fitContinuous or phylosig (package phytools, Revell 2012)....
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References
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TL;DR: UNLABELLED Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics that provides both utility functions for reading and writing data and manipulating phylogenetic trees.
Abstract: Summary: Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics. APE provides both utility functions for reading and writing data and manipulating phylogenetic trees, as well as several advanced methods for phylogenetic and evolutionary analysis (e.g. comparative and population genetic methods). APE takes advantage of the many R functions for statistics and graphics, and also provides a flexible framework for developing and implementing further statistical methods for the analysis of evolutionary processes.
Availability: The program is free and available from the official R package archive at http://cran.r-project.org/src/contrib/PACKAGES.html#ape. APE is licensed under the GNU General Public License.
10,818 citations
01 Jan 2006
TL;DR: Platform-independent and open source igraph aims to satisfy all the requirements of a graph package while possibly remaining easy to use in interactive mode as well.
Abstract: There is no other package around that satisfies all the following requirements: •Ability to handle large graphs efficiently •Embeddable into higher level environments (like R [6] or Python [7]) •Ability to be used for quick prototyping of new algorithms (impossible with “click & play” interfaces) •Platform-independent and open source igraph aims to satisfy all these requirements while possibly remaining easy to use in interactive mode as well.
8,850 citations
"phytools: an R package for phylogen..." refers background in this paper
...These include the following packages: animation: Xie (2011); calibrate: Graffelman (2010); igraph: Csardi & Nepusz (2006); mnormt: Genz & Azzalini (2011); msm: Jackson (2011); numDeriv: Gilbert (2011); quadprog: Turlach &Weingessel (2010)....
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TL;DR: A method of correcting for the phylogeny has been proposed, which specifies a set of contrasts among species, contrasts that are statistically independent and can be used in regression or correlation studies.
Abstract: Recent years have seen a growth in numerical studies using the comparative method. The method usually involves a comparison of two phenotypes across a range of species or higher taxa, or a comparison of one phenotype with an environmental variable. Objectives of such studies vary, and include assessing whether one variable is correlated with another and assessing whether the regression of one variable on another differs significantly from some expected value. Notable recent studies using statistical methods of this type include Pilbeam and Gould's (1974) regressions of tooth area on several size measurements in mammals; Sherman's (1979) test of the relation between insect chromosome numbers and social behavior; Damuth's (1981) investigation of population density and body size in mammals; Martin's (1981) regression of brain weight in mammals on body weight; Givnish's (1982) examination of traits associated with dioecy across the families of angiosperms; and Armstrong's (1983) regressions of brain weight on body weight and basal metabolism rate in mammals. My intention is to point out a serious statistical problem with this approach, a problem that affects all of these studies. It arises from the fact that species are part of a hierarchically structured phylogeny, and thus cannot be regarded for statistical purposes as if drawn independently from the same distribution. This problem has been noticed before, and previous suggestions of ways of coping with it are briefly discussed. The nonindependence can be circumvented in principle if adequate information on the phylogeny is available. The information needed to do so and the limitations on its use will be discussed. The problem will be discussed and illustrated with reference to continuous variables, but the same statistical issues arise when one or both of the variables are discrete, in which case the statistical methods involve contingency tables rather than regressions and correlations.
8,833 citations
"phytools: an R package for phylogen..." refers background in this paper
...In recent decades, phylogenies have assumed a central role in evolutionary biology (Felsenstein 1985, 2004; Harvey & Pagel 1991; Losos 2011)....
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Book•
01 Jan 1991
TL;DR: The comparative method for studying adaptation why worry about phylogeny?
Abstract: The comparative method for studying adaptation why worry about phylogeny? reconstructing phylogenetic trees and ancestral character states comparative analysis of discrete data comparative analysis of continuous variables determining the form of comparative relationships.
5,197 citations
"phytools: an R package for phylogen..." refers background in this paper
...In recent decades, phylogenies have assumed a central role in evolutionary biology (Felsenstein 1985, 2004; Harvey & Pagel 1991; Losos 2011)....
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TL;DR: The combination of these phylogenies with powerful new statistical approaches for the analysis of biological evolution is challenging widely held beliefs about the history and evolution of life on Earth.
Abstract: Phylogenetic trees describe the pattern of descent amongst a group of species. With the rapid accumulation of DNA sequence data, more and more phylogenies are being constructed based upon sequence comparisons. The combination of these phylogenies with powerful new statistical approaches for the analysis of biological evolution is challenging widely held beliefs about the history and evolution of life on Earth.
4,159 citations
"phytools: an R package for phylogen..." refers methods in this paper
...phylosig Computes phylogenetic signal using two different methods (Pagel 1999; Freckleton, Harvey & Pagel 2002; Blomberg, Garland & Ives 2003) and incorporating sampling error (Ives, Midford & Garland 2007) plotSimmap Plots a stochastic character map format tree (Fig....
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