期刊
GENETICS
卷 196, 期 1, 页码 253-+出版社
GENETICS SOC AM
DOI: 10.1534/genetics.113.157172
关键词
-
资金
- Life Sciences Interface Doctoral Training Centre
- Engineering and Physical Sciences Research Council
- UK Clinical Research Collaboration (UKCRC) Modernising Medical Microbiology Consortium
- Wellcome Trust [087646/Z/08/Z]
- Medical Research Council
- Biotechnology and Biological Sciences Research Council
- National Institute for Health Research on behalf of the Department of Health [G0800778]
- Wellcome Trust [087646/Z/08/Z] Funding Source: Wellcome Trust
- MRC [MR/K010174/1, G0800778] Funding Source: UKRI
- Medical Research Council [MR/K010174/1, MR/K010174/1B, G0800778] Funding Source: researchfish
- National Institute for Health Research [NF-SI-0512-10047] Funding Source: researchfish
Patterns of linkage disequilibrium, homoplasy, and incompatibility are difficult to interpret because they depend on several factors, including the recombination process and the population structure. Here we introduce a novel model-based framework to infer recombination properties from such summary statistics in bacterial genomes. The underlying model is sequentially Markovian so that data can be simulated very efficiently, and we use approximate Bayesian computation techniques to infer parameters. As this does not require us to calculate the likelihood function, the model can be easily extended to investigate less probed aspects of recombination. In particular, we extend our model to account for the bias in the recombination process whereby closely related bacteria recombine more often with one another. We show that this model provides a good fit to a data set of Bacillus cereus genomes and estimate several recombination properties, including the rate of bias in recombination. All the methods described in this article are implemented in a software package that is freely available for download at http://code.google.com/p/clonalorigin/.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据