Hierarchical and Spatially Explicit Clustering of DNA Sequences with BAPS Software

被引:476
作者
Cheng, Lu [1 ]
Connor, Thomas R. [2 ,4 ]
Siren, Jukka [1 ]
Aanensen, David M. [3 ]
Corander, Jukka [1 ]
机构
[1] Univ Helsinki, Dept Math & Stat, Helsinki, Finland
[2] Cardiff Univ, Cardiff Sch Biosci, Cardiff CF10 3AX, S Glam, Wales
[3] Univ London Imperial Coll Sci Technol & Med, Dept Infect Dis Epidemiol, London, England
[4] Sanger Inst, Cambridge, England
基金
芬兰科学院; 欧洲研究理事会;
关键词
genetic population structure; phylogeographics; Bayesian inference; evolutionary epidemiology; POPULATION-STRUCTURE; RECOMBINATION; ORIGIN; MODEL; MLST;
D O I
10.1093/molbev/mst028
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
070307 [化学生物学]; 071010 [生物化学与分子生物学];
摘要
Phylogeographical analyses have become commonplace for a myriad of organisms with the advent of cheap DNA sequencing technologies. Bayesian model-based clustering is a powerful tool for detecting important patterns in such data and can be used to decipher even quite subtle signals of systematic differences in molecular variation. Here, we introduce two upgrades to the Bayesian Analysis of Population Structure (BAPS) software, which enable 1) spatially explicit modeling of variation in DNA sequences and 2) hierarchical clustering of DNA sequence data to reveal nested genetic population structures. We provide a direct interface to map the results from spatial clustering with Google Maps using the portal http://www.spatialepidemiology.net/ and illustrate this approach using sequence data from Borrelia burgdorferi. The usefulness of hierarchical clustering is demonstrated through an analysis of the metapopulation structure within a bacterial population experiencing a high level of local horizontal gene transfer. The tools that are introduced are freely available at http://www.helsinki.fi/bsg/software/BAPS/.
引用
收藏
页码:1224 / 1228
页数:5
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