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netview p : a network visualization tool to unravel complex population structure using genome‐wide SNP s
Author(s) -
Steinig Eike J.,
Neuditschko Markus,
Khatkar Mehar S.,
Raadsma Herman W.,
Zenger Kyall R.
Publication year - 2016
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.12442
Subject(s) - biology , single nucleotide polymorphism , population , python (programming language) , computational biology , snp , genome , genetics , computer science , gene , operating system , demography , sociology , genotype
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 SNP s. The program is cross‐platform compatible, open‐source and efficiently operates on data ranging from hundreds to hundreds of thousands of SNP s. The pipeline was used for the analysis of pedigree data from simulated ( n = 750, SNP s = 1279) and captive silver‐lipped pearl oysters ( n = 415, SNP s = 1107), wild populations of the European hake from the Atlantic and Mediterranean ( n = 834, SNP s = 380) and grey wolves from North America ( n = 239, SNP s = 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 .