SUMMARY: ipyrad is a free and open source tool for assembling and analyzing restriction site-associated DNA sequence datasets using de novo and/or reference-based approaches. It is designed to be massively scalable to hundreds of taxa and thousands of samples, and can be efficiently parallelized on high performance computing clusters. It is available both as a command line interface and as a Python package with an application programming interface, the latter of which can be used interactively to write complex, reproducible scripts and implement a suite of downstream analysis tools. AVAILABILITY AND IMPLEMENTATION: ipyrad is a free and open source program written in Python. Source code is available from the GitHub repository (https://github.com/dereneaton/ipyrad/), and Linux and MacOS installs are distributed through the conda package manager. Complete documentation, including numerous tutorials, and Jupyter notebooks demonstrating example assemblies and applications of downstream analysis tools are available online: https://ipyrad.readthedocs.io/.

SUMMARY: ipcoal is a free and open source Python package for simulating and analyzing genealogies and sequences. It automates the task of describing complex demographic models (e.g. with divergence times, effective population sizes, migration events) to the msprime coalescent simulator by parsing a user-supplied species tree or network. Genealogies, sequences and metadata are returned in tabular format allowing for easy downstream analyses. ipcoal includes phylogenetic inference tools to automate gene tree inference from simulated sequence data, and visualization tools for analyzing results and verifying model accuracy. The ipcoal package is a powerful tool for posterior predictive data analysis, for methods validation and for teaching coalescent methods in an interactive and visual environment. AVAILABILITY AND IMPLEMENTATION: Source code is available from the GitHub repository (https://github.com/pmckenz1/ipcoal/) and is distributed for packaged installation with conda. Complete documentation and interactive notebooks prepared for teaching purposes, including an empirical example, are available at https://ipcoal.readthedocs.io/. CONTACT: [email protected].

MOTIVATION: Restriction-site-associated genomic markers are a powerful tool for investigating evolutionary questions at the population level, but are limited in their utility at deeper phylogenetic scales where fewer orthologous loci are typically recovered across disparate taxa. While this limitation stems in part from mutations to restriction recognition sites that disrupt data generation, an additional source of data loss comes from the failure to identify homology during bioinformatic analyses. Clustering methods that allow for lower similarity thresholds and the inclusion of indel variation will perform better at assembling RADseq loci at the phylogenetic scale. RESULTS: PyRAD is a pipeline to assemble de novo RADseq loci with the aim of optimizing coverage across phylogenetic datasets. It uses a wrapper around an alignment-clustering algorithm, which allows for indel variation within and between samples, as well as for incomplete overlap among reads (e.g. paired-end). Here I compare PyRAD with the program Stacks in their performance analyzing a simulated RADseq dataset that includes indel variation. Indels disrupt clustering of homologous loci in Stacks but not in PyRAD, such that the latter recovers more shared loci across disparate taxa. I show through reanalysis of an empirical RADseq dataset that indels are a common feature of such data, even at shallow phylogenetic scales. PyRAD uses parallel processing as well as an optional hierarchical clustering method, which allows it to rapidly assemble phylogenetic datasets with hundreds of sampled individuals. AVAILABILITY: Software is written in Python and freely available at http://www.dereneaton.com/software/.