Model adequacy tests for probabilistic models of chromosome-number evolution

Anna Rice, Itay Mayrose*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Chromosome number is a central feature of eukaryote genomes. Deciphering patterns of chromosome-number change along a phylogeny is central to the inference of whole genome duplications and ancestral chromosome numbers. ChromEvol is a probabilistic inference tool that allows the evaluation of several models of chromosome-number evolution and their fit to the data. However, fitting a model does not necessarily mean that the model describes the empirical data adequately. This vulnerability may lead to incorrect conclusions when model assumptions are not met by real data. Here, we present a model adequacy test for likelihood models of chromosome-number evolution. The procedure allows us to determine whether the model can generate data with similar characteristics as those found in the observed ones. We demonstrate that using inadequate models can lead to inflated errors in several inference tasks. Applying the developed method to 200 angiosperm genera, we find that in many of these, the best-fitting model provides poor fit to the data. The inadequacy rate increases in large clades or in those in which hybridizations are present. The developed model adequacy test can help researchers to identify phylogenies whose underlying evolutionary patterns deviate substantially from current modelling assumptions and should guide future methods development.

Original languageEnglish
Pages (from-to)3602-3613
Number of pages12
JournalNew Phytologist
Volume229
Issue number6
DOIs
StatePublished - Mar 2021

Funding

FundersFunder number
Edmond J. Safra Center for Bioinformatics
National Science Foundation1655478
Israel Science Foundation
Tel Aviv University961/17

    Keywords

    • chromEvol
    • chromosome number
    • dysploidy
    • model adequacy
    • model selection
    • model testing
    • phylogenetics
    • polyploidy

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