NETVIEW P: a network visualization tool to unravel complex population structure using genome-wide SNPs

作者：Steinig Eike J^*; Neuditschko Markus; Khatkar Mehar S; Raadsma Herman W; Zenger Kyall R

来源：Molecular Ecology Resources, 2016, 16(1): 216-227.

DOI：10.1111/1755-0998.12442

• graph theory
• NETVIEW
• network analysis
• population genetics
• SNP
• wild and captive populations

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.

• 出版日期2016-1