Genomics LAndscape of Divergence Simulations

The R package ‘glads’ is an individual-based framework for forward demographic, genetic and genomic simulations

The main aim is to simulate the divergence of populations further in time, elucidating genomic patterns that may be generated by a range of demographic and genetic scenarios.

Integrating the program into an Approximate Bayesian Computation (ABC) framework or a similar approach enables the exploration of hypotheses on empirical observations. The framework is valuable for any genotype-phenotype map and any genomic architecture, considering the deterministic and stochastic process for any biological system.

How to cite ‘glads’?

Quilodrán CS, Kristen Ruegg, Sendell-Price AT, Anderson EC, Coulson T, Clegg SM (2020). The multiple population genetic and demographic routes to islands of genomic divergence. Methods in Ecology and Evolution, 11(1), 6-21.

Main features of ‘glads’

  • Simulation of different types of selection and neutral evolution
  • Flexible fitness function for genotype x phenotype x environmental interactions
  • Analysis of multiple populations
  • Consideration of genomes specificities—for instance, inclusion of genomic regions of high linkage, genes of large effect and multiple polymorphisms

New in the beta version

  • Interaction between different populations and taxa
  • Populations evolving with different fitness functions
  • Easier retrieval of the output at user-defined generations
  • Different migration regimes through time

Methods Blog: A new evolutionary simulation R package sheds light on the metaphor of genomic islands of divergence

Imagine a songbird hatching on a small island in the Pacific Ocean. There is little chance that this bird will survive to sexual maturity and reproduce. However, if it does, this bird will contribute to the genetic diversity of the following generation, and potentially have an influence on the population’s evolutionary trajectory.

(Conitnue reading here)

Example of papers using ‘glads’

The following published manuscripts performed computational simulations using ‘glads’. The custom R codes are provided in supporting information.

Genes | Genomes | Genetics

Sendell-Price AT et al. (2020)

Molecular Ecology

Ali AAH et al. (2023)

Molecular Biology and Evolution

Di Santo NL et al. (2023)

Molecular Ecology Resources

Quilodrán CS et al. (2023)

Bug report

If you encounter any bug using ‘glads’, please email Claudio S. Quilodrán.