SnappNet

SnappNet is a software tool for inferring phylogenetic networks from biallelic markers under the multispecies coalescent model in networks (MSNC). It extends the Snapp method, which infers evolutionary trees, to handle reticulate events such as horizontal gene transfer, hybridization, and introgression. SnappNet uses a novel and efficient algorithm for computing the likelihood of biallelic markers, making it suitable for analyzing large datasets.

Key features of SnappNet:

1. Implemented as a package in the popular BEAST 2 software.
2. Uses a Bayesian framework to sample networks and compute priors.
3. Exponentially more time-efficient than MCMC_BiMarkers, another method that extends Snapp to networks, especially for complex network scenarios.
4. Demonstrates similar accuracy to MCMC_BiMarkers for simple networks and higher accuracy for more complex networks.
5. Significantly faster than MCMC_BiMarkers in likelihood computation for complex networks. SnappNet has been tested on simulated data and applied to a rice dataset, providing consistent results with previous findings and offering additional insights into rice evolution. In summary, SnappNet is an accurate and efficient tool for inferring phylogenetic networks from biallelic markers, particularly well-suited for analyzing large datasets and complex evolutionary scenarios.