Back

bigrig: A range simulator for the DEC model

Bettisworth, B.; Stamatakis, A.

2025-12-01 bioinformatics
10.1101/2025.11.24.690345 bioRxiv
Show abstract

Quality software tools for science are, as a necessity, rigorously tested and verified. However, there is a major challenge to testing software used for phylogenetics and similar analysis. There is a shortage of ground truth data which can be used for validation, resulting in a reliance on simulated data. This reliance on simulated data results in a second challenge: the verification of the tool which generates the simulated data. In historical biogeography, software which simulated data has exclusively been implemented on an ad-hoc basis to verify specific tools. Here, we introduce bigrig, a simulator for the DEC[+J] model of range evolution. We show that bigrig is correct with extremely rigorous statistical testing and validation, ensuring that results deviate by no more than 0.0001 with 99.999% confidence. We also show that bigrig is extremely fast, capable of generating data for trees with tens of thousands of tips in under a second.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.