autoStreamTree: Genomic variant data fitted to geospatial networks

Abstract

SummaryLandscape genetics is a statistical framework that parses genetic variation within the context of spatial covariates, but current analytical methods typically fail to accommodate the unique topologies and autocorrelations inherent to network-configured habitats (e.g., streams or rivers). autoStreamTree analyzes and visualizes genome-wide variation across dendritic networks (i.e., riverscapes). Availability and ImplementationautoStreamTree is an open source workflow (https://github.com/tkchafin/autostreamtree) that automatically extracts a minimal graph representation of a geospatial network from a provided shapefile, then fits the components of genetic variation using a least-squares algorithm. To facilitate downstream population genomic analyses, genomic variation can be represented per-locus, per-SNP, or via microhaplotypes (i.e., phased data). We demonstrate the workflow by quantifying genetic variation in Speckled Dace (Rhinichthys osculus) versus environmental covariates, with putative adaptive variants subsequently identified. Contacttyler.chafin@bioss.ac.uk