SV-Pop: population-based structural variant analysis and visualization

BMC Bioinformatics

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[1] 0000 0004 0425 469X, grid.8991.9, Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, WC1E 7HT, London, UK;0000 0004 0425 469X, grid.8991.9, Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, WC1E 7HT, London, UK;0000 0004 0425 469X, grid.8991.9, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, WC1E 7HT, London, UK;

关键词: Population genomics;    Structural variation;    Bioinformatics;    Analytics;    Python;    R;    Shiny;   

DOI  :  10.1186/s12859-019-2718-4

来源: publisher

【 摘 要 】

BackgroundGenetic structural variation underpins a multitude of phenotypes, with significant implications for a range of biological outcomes. Despite their crucial role, structural variants (SVs) are often neglected and overshadowed by single nucleotide polymorphisms (SNPs), which are used in large-scale analysis such as genome-wide association and population genetic studies.ResultsTo facilitate the high-throughput analysis of structural variation we have developed an analytical pipeline and visualisation tool, called SV-Pop. The utility of this pipeline was then demonstrated through application with a large, multi-population P. falciparum dataset.ConclusionsDesigned to facilitate downstream analysis and visualisation post-discovery, SV-Pop allows for straightforward integration of multi-population analysis, method and sample-based concordance metrics, and signals of selection.

【 授权许可】

CC BY