AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |
Back to Blog
Modes of evolution gtr4/8/2024 ![]() ![]() ![]() Under the frequentist approach, the fit of the data to each substitution model, together with the model parameters, tree topology, and branch lengths is assessed through iterative optimizations of the likelihood function. Selecting the most suitable model for describing the evolutionary process has been addressed under both the frequentist and Bayesian approaches, by proposing statistical criteria to compare the fit of competing models. However, the expected error of each estimate increases with the increase in the number of parameters, which is problematic mainly when data are scarce. Altogether, these produce varied alternatives that account for different processes of evolution 1, 2, 3, 4, 5, 6, 7, 8.Īccounting for more parameters grants a model the flexibility to fit different datasets and capture their complexity. ![]() Such assumptions, quantified by several parameters, determine whether the substitution rates between all pairs of nucleotides are identical or independent, whether the stationary frequencies of the nucleotides within the analyzed data are equal or allowed to vary, whether a proportion of the sites are fully conserved, and whether heterogeneous rates of evolution are allowed across the alignment sites. Over the last 50 years, a plethora of evolutionary models has been developed, each relying on a different set of assumptions regarding the dynamics of nucleotide evolution. Parameter inference, whether performed within the maximum likelihood (ML) or Bayesian inference paradigms, relies on explicit definition of the substitution process, which may vary in spatial manner (across the alignment sites) and in temporal manner (branches of the phylogeny). Probabilistic evolutionary models form the basis of sequence data analyses. ![]()
0 Comments
Read More
Leave a Reply. |