PyRAD: assembly ofde novoRADseq loci for phylogenetic analyses
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 alternative 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.PyRADis a pipeline to assemblede novoRADseq loci with the aim of optimizing coverage across phylogenetic data sets. It utilizes 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 comparePyRADwith the programStacksin their performance analyzing a simulated RADseq data set that includes indel variation. Indels disrupt clustering of homologous loci inStacksbut not inPyRAD, such that the latter recovers more shared loci across disparate taxa. I show through re-analysis of an empirical RADseq data set that indels are a common feature of such data, even at shallow phylogenetic scales.PyRADutilizes parallel processing as well as an optional hierarchical clustering method which allow it to rapidly assemble phylogenetic data sets with hundreds of sampled individuals.