netview p: a network visualization tool to unravel complex population structure using genome‐wide SNPs |
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| Authors: | Eike J. Steinig Markus Neuditschko Mehar S. Khatkar Herman W. Raadsma Kyall R. Zenger |
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| Affiliation: | 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 |
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| 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 . |
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| Keywords: | graph theory
netview
network analysis population genetics SNP wild and captive populations |
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