PalantiR

PalantiR simulates and visualizes complete substitution histories — every substitution event, with its time, codon, and fitness context — under time-heterogeneous mutation–selection codon substitution models and other advanced models, including site-specific fitness profiles, epistasis between sites, and changes in effective population size or fitness along a phylogeny.

For installation notes, see this page.

Details on particular models and simulation types can be found on the following pages:

Nucleotide Models

Codon Models

Temporal Heterogeneity

Features

What’s new in 1.3

Version 1.3 makes scaling_type = "synonymous" a dS gauge: branch lengths measure neutral synonymous substitutions per synonymous opportunity, equivalent to neutral nucleotide substitutions per site. The former synonymous-event-count convention remains available as "synonymous-per-codon". Time-heterogeneous simulations preserve the chosen currency through model shifts. See NEWS.md for the complete list, including breaking changes.

Engine validation

The simulation engine is validated by a rerunnable notebook that separately tests event-count gauges, the dS gauge under homogeneous and time-heterogeneous GY94 and mutation–selection models, the stationary distribution, and transient rescaling. Each comparison has a pre-stated statistical criterion. Read the current validation report (all tests pass under version 1.3.0), or rerun it from a clone of the repository:

# in validation/, with PalantiR installed
rmarkdown::render("engine_validation.Rmd", params = list(seed = 1))

For a larger event-level demonstration, the GY94 history-validation report simulates 5,000 codons on a 50-taxon tree, reconstructs Goldman–Yang dN/dS from all recorded substitutions, and visualizes the branch-specific histories. That historical demonstration explicitly uses the "synonymous-per-codon" event-count gauge; its opportunity-corrected dN/dS calculation remains valid. The executable Jupyter notebook is retained in the repository under validation/.

Substitution histories under mutation–selection with epistasis

A fitness shift under a time-heterogeneous mutation–selection model