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netview p: a network visualization tool to unravel complex population structure using genome‐wide SNPs
Authors:Eike J Steinig  Markus Neuditschko  Mehar S Khatkar  Herman W Raadsma  Kyall R Zenger
Institution:1. College of Marine and Environmental Sciences, James Cook University, Townsville, Qld, Australia;2. Reprogen – Animal Bioscience, Faculty of Veterinary Science, University of Sydney, Camden, NSW, Australia;3. Centre for Sustainable Tropical Fisheries and Aquaculture, Townsville, Qld, Australia
Abstract:Network‐based approaches are emerging as valuable tools for the analysis of complex genetic structure in wild and captive populations. netview p combines data quality control with the construction of population networks through mutual k‐nearest neighbours thresholds applied to genome‐wide SNPs. The program is cross‐platform compatible, open‐source and efficiently operates on data ranging from hundreds to hundreds of thousands of SNPs. The pipeline was used for the analysis of pedigree data from simulated (n = 750, SNPs = 1279) and captive silver‐lipped pearl oysters (n = 415, SNPs = 1107), wild populations of the European hake from the Atlantic and Mediterranean (n = 834, SNPs = 380) and grey wolves from North America (n = 239, SNPs = 78 255). The population networks effectively visualize large‐ and fine‐scale genetic structure within and between populations, including family‐level structure and relationships. netview p comprises a network‐based addition to other population analysis tools and provides user‐friendly access to a complex network analysis pipeline through implementation in python .
Keywords:graph theory     netview     network analysis  population genetics  SNP  wild and captive populations
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