Title: SiPhyNetwork : An R package for simulating phylogenetic networks
Abstract Gene flow is increasingly recognized as an important macroevolutionary process. The many mechanisms that contribute to gene flow (e.g. introgression, hybridization, lateral gene transfer) uniquely affect the diversification of dynamics of species, making it important to be able to account for these idiosyncrasies when constructing phylogenetic models. Existing phylogenetic‐network simulators for macroevolution are limited in the ways they model gene flow.We presentSiPhyNetwork, an R package for simulating phylogenetic networks under a birth–death‐hybridization process.Our package unifies the existing birth–death‐hybridization models while also extending the toolkit for modelling gene flow. This tool can create patterns of reticulation such as hybridization, lateral gene transfer, and introgression.Specifically, we model different reticulate events by allowing events to either add, remove or keep constant the number of lineages. Additionally, we allow reticulation events to be trait dependent, creating the ability to model the expanse of isolating mechanisms that prevent gene flow. This tool makes it possible for researchers to model many of the complex biological factors associated with gene flow in a phylogenetic context. more »« less
Abstract ThePCMBase Rpackage is a powerful computational tool that enables efficient calculations of likelihoods for a wide range of phylogenetic Gaussian models.Taking advantage of it, we redesigned theRpackagemvSLOUCH.Here, we demonstrate how the new version of the package can be used to thoroughly examine the evolution and adaptation of traits in a large dataset of 1252 vascular plants through the use of multivariate Ornstein–Uhlenbeck processes.The results of our analysis demonstrate the ability of the modelling framework to distinguish between various alternative hypotheses regarding the evolution of functional traits in angiosperms.
Gross, Elizabeth; van Iersel, Leo; Janssen, Remie; Jones, Mark; Long, Colby; Murakami, Yukihiro
(, Journal of Mathematical Biology)
Abstract Phylogenetic networks can represent evolutionary events that cannot be described by phylogenetic trees. These networks are able to incorporate reticulate evolutionary events such as hybridization, introgression, and lateral gene transfer. Recently, network-based Markov models of DNA sequence evolution have been introduced along with model-based methods for reconstructing phylogenetic networks. For these methods to be consistent, the network parameter needs to be identifiable from data generated under the model. Here, we show that the semi-directed network parameter of a triangle-free, level-1 network model with any fixed number of reticulation vertices is generically identifiable under the Jukes–Cantor, Kimura 2-parameter, or Kimura 3-parameter constraints.
Gurarie, Eliezer; Thompson, Peter R.; Kelly, Allicia P.; Larter, Nicholas C.; Fagan, William F.; Joly, Kyle; Graham, ed., Laura
(, Methods in Ecology and Evolution)
Abstract Many important demographic processes are seasonal, including survival. For many species, mortality risk is significantly higher at certain times of the year than at others, whether because resources are scarce, susceptibility to predators or disease is high, or both. Despite the importance of survival modelling in wildlife sciences, no tools are available to estimate the peak, duration and relative importance of these ‘seasons of mortality’.We presentcyclomort, anrpackage that estimates the timing, duration and intensity of any number of mortality seasons with reliable confidence intervals. The package includes a model selection approach to determine the number of mortality seasons and to test whether seasons of mortality vary across discrete grouping factors.We illustrate the periodic hazard function model and workflow of cyclomort with simulated data. We then estimate mortality seasons of two caribouRangifer taranduspopulations that have strikingly different mortality patterns, including different numbers and timing of mortality peaks, and a marked change in one population over time.Thecyclomortpackage was developed to estimate mortality seasons for wildlife, but the package can model any time‐to‐event processes with a periodic component.
Baken, Erica K.; Collyer, Michael L.; Kaliontzopoulou, Antigoni; Adams, Dean C.
(, Methods in Ecology and Evolution)
Abstract Geometric morphometric (GM) tools are essential for meaningfully quantifying and understanding patterns of variation in complex traits like shape. In this field, the breadth of answerable questions has grown dramatically in recent years through the development of new analyses and increased computational efficiency.In this note, we describe the ways in whichgeomorph, a widely usedRpackage for quantifying and analysing GM data, has grown with the field.We presentgeomorph v4.0and describe the ways in which this version has dramatically improved upon previous versions. We also present a new graphical user interface for easy implementation,gmShiny.These contributions positiongeomorphto be the primary tool for GM analyses, particularly those employing a phylogenetic comparative approach.
Papadopoulou, Marina; Garnier, Simon; King, Andrew_J
(, Methods in Ecology and Evolution)
Abstract Collective motion, that is the coordinated spatial and temporal organisation of individuals, is a core element in the study of collective animal behaviour. The self‐organised properties of how a group moves influence its various behavioural and ecological processes, such as predator–prey dynamics, social foraging and migration. However, little is known about the inter‐ and intra‐specific variation in collective motion. Despite the significant advancement in high‐resolution tracking of multiple individuals within groups, providing collective motion data for animals in the laboratory and the field, a framework to perform quantitative comparisons across species and contexts is lacking.Here, we present theswaRmversepackage. Building on two existing R packages,trackdfandswaRm,swaRmverseenables the identification and analysis of collective motion ‘events’, as presented in Papadopoulou et al. (2023), creating a unit of comparison across datasets. We describe the package's structure and showcase its functionality using existing datasets from several species and simulated trajectories from an agent‐based model.From positional time‐series data for multiple individuals (x‐y‐t‐id),swaRmverseidentifies events of collective motion based on the distribution of polarisation and group speed. For each event, a suite of validated biologically meaningful metrics are calculated, and events are placed into a ‘swarm space’ through dimensional reduction techniques.Our package provides the first automated pipeline enabling the analysis of data on collective behaviour. The package allows the calculation and use of complex metrics for users without a strong quantitative background and will promote communication and data‐sharing across disciplines, standardising the quantification of collective motion across species and promoting comparative investigations.
Justison, Joshua A., Solis‐Lemus, Claudia, and Heath, Tracy A. SiPhyNetwork : An R package for simulating phylogenetic networks. Methods in Ecology and Evolution 14.7 Web. doi:10.1111/2041-210X.14116.
Justison, Joshua A., Solis‐Lemus, Claudia, & Heath, Tracy A. SiPhyNetwork : An R package for simulating phylogenetic networks. Methods in Ecology and Evolution, 14 (7). https://doi.org/10.1111/2041-210X.14116
Justison, Joshua A., Solis‐Lemus, Claudia, and Heath, Tracy A.
"SiPhyNetwork : An R package for simulating phylogenetic networks". Methods in Ecology and Evolution 14 (7). Country unknown/Code not available: Wiley-Blackwell. https://doi.org/10.1111/2041-210X.14116.https://par.nsf.gov/biblio/10413317.
@article{osti_10413317,
place = {Country unknown/Code not available},
title = {SiPhyNetwork : An R package for simulating phylogenetic networks},
url = {https://par.nsf.gov/biblio/10413317},
DOI = {10.1111/2041-210X.14116},
abstractNote = {Abstract Gene flow is increasingly recognized as an important macroevolutionary process. The many mechanisms that contribute to gene flow (e.g. introgression, hybridization, lateral gene transfer) uniquely affect the diversification of dynamics of species, making it important to be able to account for these idiosyncrasies when constructing phylogenetic models. Existing phylogenetic‐network simulators for macroevolution are limited in the ways they model gene flow.We presentSiPhyNetwork, an R package for simulating phylogenetic networks under a birth–death‐hybridization process.Our package unifies the existing birth–death‐hybridization models while also extending the toolkit for modelling gene flow. This tool can create patterns of reticulation such as hybridization, lateral gene transfer, and introgression.Specifically, we model different reticulate events by allowing events to either add, remove or keep constant the number of lineages. Additionally, we allow reticulation events to be trait dependent, creating the ability to model the expanse of isolating mechanisms that prevent gene flow. This tool makes it possible for researchers to model many of the complex biological factors associated with gene flow in a phylogenetic context.},
journal = {Methods in Ecology and Evolution},
volume = {14},
number = {7},
publisher = {Wiley-Blackwell},
author = {Justison, Joshua A. and Solis‐Lemus, Claudia and Heath, Tracy A.},
}
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