Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 42 min ago
Peer-reviewedCC BY 4.0Methods in Ecology and Evolution

MorphSim : An R package for simulating discrete morphological data

Abstract

1. Morphological data are essential for reconstructing evolutionary histories, particularly for fossil taxa, as they represent the primary source of information for integrating extinct lineages into phylogenetic analyses. Despite this, tools for simulating realistic morphological datasets for fossil-inclusive phylogenetic workflows remain limited. 2. We introduce MorphSim, an R package for simulating discrete morphological characters specifically designed for total-evidence and tip-dated phylogenetic analyses, focusing on the morphological component. It generates synthetic datasets that closely match the structure of empirical morphological matrices, accommodating diverse character coding designs and biologically structured missing data reflecting taphonomic preservation biases. 3. MorphSim integrates directly with TreeSim, FossilSim and SimClock, providing a complete end-to-end pipeline for generating datasets compatible with Bayesian total-evidence dating software such as RevBayes and BEAST2. This enables simulation of complex, biologically informed datasets spanning deep timescales, incorporating both extinct and extant lineages. It implements the Mk model and its extensions, including among-character rate variation and user-defined rate matrices, across single and multi-partition schemes. 4. Additionally, we developed MorphSimShiny, an interactive Shiny application providing a beginner-friendly interface for exploring model assumptions and simulating morphological datasets without requiring familiarity with R.

Related

  1. Machine Learning-Driven Cellular Automata for Simulating Plant Growth Regulator-Optimized Callus Induction in Caladium bicolor
    Luzhen Zhao, Feng Hu, Mei Li +2
    Plants (Basel, Switzerland)Peer-reviewedCC BYFull textPlant biologyEurope PMC
  2. Protocol for simulating cell-contact dynamics of proliferating epithelia using the vertex model
    Tanmoy Sarkar, Jeffrey J Lovelace, Matej Krajnc +2
    STAR ProtocolsPeer-reviewedCC BY-NC-ND 4.0Full textCell biologyPMCEurope PMC
  3. Uncertainties in simulating wheat growth responses to waterlogging
    Rogério de S Nóia-Júnior, Matthew Tom Harrison, Taru Palosuo +37
    Agricultural Water ManagementPeer-reviewedCC BY 4.0Full textPlant biologyHAL
  4. Img2EEG: A Scalable and Interpretable Encoding Framework for Simulating Human EEG Responses to Visual Inputs
    Z. Lu, J. D. Golomb
    bioRxivPreprintCC BY-NC-NDFull textNeurosciencebioRxiv
  5. Predicting the Efficacy of Myopia Control Spectacle Lenses by Simulating Their Optical Effect on the Retina
    S. Hamlaoui, S. Goethals, K. Baranton +3
    bioRxivPreprintCC BY-NC-NDFull textNeurosciencebioRxiv
BibTeX
@article{mulvey2026morphsim,
  title = {{MorphSim : An R package for simulating discrete morphological data}},
  author = {Laura P A Mulvey and Tim Brandler and Alessio Capobianco and Rachel C M Warnock and Joëlle Barido‐sottani},
  journal = {Methods in Ecology and Evolution},
  year = {2026},
  month = may,
  doi = {10.1111/2041-210x.70326},
  url = {https://hal.science/hal-05780767v1},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - MorphSim : An R package for simulating discrete morphological data
AU  - Laura P A Mulvey
AU  - Tim Brandler
AU  - Alessio Capobianco
AU  - Rachel C M Warnock
AU  - Joëlle Barido‐sottani
PY  - 2026
DA  - 2026/05/22
JO  - Methods in Ecology and Evolution
DO  - 10.1111/2041-210x.70326
UR  - https://hal.science/hal-05780767v1
AB  - 1. Morphological data are essential for reconstructing evolutionary histories, particularly for fossil taxa, as they represent the primary source of information for integrating extinct lineages into phylogenetic analyses. Despite this, tools for simulating realistic morphological datasets for fossil-inclusive phylogenetic workflows remain limited. 2. We introduce MorphSim, an R package for simulating discrete morphological characters specifically designed for total-evidence and tip-dated phylogenetic analyses, focusing on the morphological component. It generates synthetic datasets that closely match the structure of empirical morphological matrices, accommodating diverse character coding designs and biologically structured missing data reflecting taphonomic preservation biases. 3. MorphSim integrates directly with TreeSim, FossilSim and SimClock, providing a complete end-to-end pipeline for generating datasets compatible with Bayesian total-evidence dating software such as RevBayes and BEAST2. This enables simulation of complex, biologically informed datasets spanning deep timescales, incorporating both extinct and extant lineages. It implements the Mk model and its extensions, including among-character rate variation and user-defined rate matrices, across single and multi-partition schemes. 4. Additionally, we developed MorphSimShiny, an interactive Shiny application providing a beginner-friendly interface for exploring model assumptions and simulating morphological datasets without requiring familiarity with R.
SN  - 2041-210X
SN  - 2041-210X
ER  -