SNaQ: Maximum pseudolikelihood estimation of species network

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Overview

SNaQ implements the statistical inference method in Solís-Lemus and Ané (2016). The procedure involves a numerical optimization of branch lengths and inheritance probabilities, and a heuristic search in the space of level-1 phylogenetic networks.

To get help, check

• the latest SNaQ documentation
• the latest PhyloNetworks documentation
• PhyloUtilities with a step-by-step tutorial from multi-locus sequences to necessary input for SNaQ
• tutorial for SNaQ estimation (from a 2023 workshop)
• the JuliaPhylo google group for common questions. Join the group to post/email your questions, or to receive information on new versions, bugs fixed, etc.
• search for answers in github issues and post a new issue to post a question or a report potential bugs.

Overview

SNaQ implements the statistical inference method in Solís-Lemus and Ané (2016). The procedure involves a numerical optimization of branch lengths and inheritance probabilities, and a heuristic search in the space of level-1 phylogenetic networks.

To get help, check

• the latest SNaQ documentation
• the latest PhyloNetworks documentation
• a wiki for a step-by-step tutorial with background on networks (last revised 2022)
• tutorial for comparative methods, including network calibration (2023 workshop)
• the google group for common questions. Join the group to post/email your questions, or to receive information on new versions, bugs fixed, etc.

Citing

For the SNaQ method in particular, please cite

• Claudia Solís-Lemus and Cécile Ané (2016). Inferring Phylogenetic Networks with Maximum Pseudolikelihood under Incomplete Lineage Sorting. PLoS Genet 12(3):e1005896. doi:10.1371/journal.pgen.1005896

For the PhyloNetworks package, please cite:

• Claudia Solís-Lemus, Paul Bastide and Cécile Ané (2017). PhyloNetworks: a package for phylogenetic networks. Molecular Biology and Evolution 34(12):3292–3298. doi:10.1093/molbev/msx235

See CITATION.bib for the relevant reference(s).