| Summary: | Network-based approaches are emerging as valuable tools for the analysis of complex genetic structure in both wild and captive populations. NetView P combines data quality control with the construction of population networks based on 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 through multiprocessing in Python. We used the pipeline 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 Gray Wolves from North America (n = 239, SNPs = 86,103). 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. Oyster DataArchive containing data for P. maxima analysis with NetView P, including wild (n = 83, SNPs = 999), captive (n = 684, SNPs = 834) and simulated (n = 3000, SNPs = 1271) genotypes, as well as input files (PED/MAP), node attributes and networks for visualization in Cytoscape.oyster_data.zip
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