| Literature DB >> 26129944 |
Eike J Steinig1, Markus Neuditschko2, Mehar S Khatkar2,3, Herman W Raadsma1,2,3, Kyall R Zenger1,3.
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.Entities:
Keywords: SNP; graph theory; netview; network analysis; population genetics; wild and captive populations
Mesh:
Year: 2015 PMID: 26129944 DOI: 10.1111/1755-0998.12442
Source DB: PubMed Journal: Mol Ecol Resour ISSN: 1755-098X Impact factor: 7.090