Phylogenetic inference under recombination using Bayesian stochastic topology selection.
Phylogenetic inference under recombination using Bayesian stochastic topology selection.
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DOI：
10.1093/bioinformatics/btn607
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发表时间：
2009-01-15
期刊：
影响因子：
5.8
通讯作者：
Holmes, Chris C.
中科院分区：
文献类型：
--
作者：
Webb, Alex;Hancock, John M.;Holmes, Chris C.
动机：传统的系统发育分析，用于表征类群之间的相关性，通常假设一个单一的关系存在于物种之间的每一个位点沿着基因组。这种假设没有考虑到重组，这是产生多样性的基本过程，并可能导致虚假的结果。分化诱导了一个局部的系统发育结构，该结构可能沿着基因组变化。在这里，我们概括了一个隐马尔可夫模型（HMM），以推断变化的遗传沿着多个序列比对，同时占率异质性;隐藏的状态是指未观察到的遗传拓扑结构的相关性在基因组位置。隐藏状态（拓扑）的数量和它们的结构的维数是随机的（先验未知），并使用马尔可夫链蒙特卡罗算法进行采样。HMM结构允许我们分析地整合出拓扑中所有可能的变化点以及所有未知的分支长度。结果如下：我们证明了我们的方法模拟数据，也怀疑HIV重组株的基因组，以及调查重组的15个实验室小鼠株的序列Perlegen科学测序。我们的研究结果表明，我们的方法使我们能够区分率的异质性和重组引起的遗传变异，而不限于4分类群的数据。可用性：该方法已在JAVA中实现，并且可以从http://www.stats.ox.ac.uk/~webb获得沿着本文研究的数据。联系方式：cholmes@stats.ox.ac.uk补充信息：补充数据可在生物信息学在线获得。
Motivation: Conventional phylogenetic analysis for characterizing the relatedness between taxa typically assumes that a single relationship exists between species at every site along the genome. This assumption fails to take into account recombination which is a fundamental process for generating diversity and can lead to spurious results. Recombination induces a localized phylogenetic structure which may vary along the genome. Here, we generalize a hidden Markov model (HMM) to infer changes in phylogeny along multiple sequence alignments while accounting for rate heterogeneity; the hidden states refer to the unobserved phylogenic topology underlying the relatedness at a genomic location. The dimensionality of the number of hidden states (topologies) and their structure are random (not known a priori) and are sampled using Markov chain Monte Carlo algorithms. The HMM structure allows us to analytically integrate out over all possible changepoints in topologies as well as all the unknown branch lengths. Results: We demonstrate our approach on simulated data and also to the genome of a suspected HIV recombinant strain as well as to an investigation of recombination in the sequences of 15 laboratory mouse strains sequenced by Perlegen Sciences. Our findings indicate that our method allows us to distinguish between rate heterogeneity and variation in phylogeny caused by recombination without being restricted to 4-taxa data. Availability: The method has been implemented in JAVA and is available, along with data studied here, from http://www.stats.ox.ac.uk/~webb. Contact: cholmes@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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