2018/12/10 by Krzysztof Bartoszek, Pietro Liò, Píetro Lió · 10 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Earth and Planetary Sciences · Mathematics · #Algorithm #Approximate Bayesian computation #Artificial intelligence #Bayesian probability #Biology #Computation #Computer science #Evolution and Paleontology Studies #Evolutionary biology #Field (mathematics) #Genetic algorithm #Genetics #Genomics and Phylogenetic Studies #Machine learning #Mathematics #Phylogenetic tree #Physics #Set (abstract data type) #Single-cell and spatial transcriptomics #Statistical physics #Theoretical computer science #Trait #cs.LG #msc:62F15 #msc:62P10 #msc:65C05 #msc:92-08 #msc:92B10 #q-bio.PE #stat.AP #stat.ML
paper · pdf · doi:10.5506/aphyspolbsupp.12.25
published in Acta Physica Polonica B Proceedings Supplement 12(1), 25 (Jagiellonian University)
arxiv created 2018/12/10 · openalex publication_date 2019/01/01 · arxiv updated 2020/11/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Phylogeny is the field of modelling the temporal discrete dynamics of speciation. Complex models can nowadays be studied using the Approximate Bayesian Computation approach which avoids likelihood calculations. The field's progression is hampered by the lack of robust software to estimate the numerous parameters of the speciation process. In this work we present an R package, pcmabc, based on Approximate Bayesian Computations, that implements three novel phylogenetic algorithms for trait-dependent speciation modelling. Our phylogenetic comparative methodology takes into account both the simulated traits and phylogeny, attempting to estimate the parameters of the processes generating the phenotype and the trait. The user is not restricted to a predefined set of models and can specify a variety of evolutionary and branching models. We illustrate the software with a simulation-reestimation study focused around the branching Ornstein-Uhlenbeck process, where the branching rate depends non-linearly on the value of the driving Ornstein-Uhlenbeck process. Included in this work is a tutorial on how to use the software.