Enabling Inference for Context-Dependent Models of Mutation by Bounding the Propagation of Dependency.
Enabling Inference for Context-Dependent Models of Mutation by Bounding the Propagation of Dependency.
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通过限制依赖性的传播来实现上下文相关的突变模型的推理。
DOI：
10.1089/cmb.2021.0644
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Ralph,PeterL
中科院分区：
文献类型：
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作者：
Matsen4th,FrederickA;Ralph,PeterL
虽然基因组中位置突变的速率已知不仅取决于待突变的核苷酸，而且还取决于相邻的核苷酸，但是使用上下文依赖性突变的模型进行系统发育推断仍然具有挑战性。在这些模型中，一个突变的影响原则上可能传播到遥远的位置，使得难以计算精确的可能性。这篇文章展示了如何使用依赖性传播的界限来计算给定基因组片段的突变可能性，通过边缘化足够长的侧翼序列。这可以用于最大似然或贝叶斯推断。还讨论了检查残差和迭代模型改进的协议。在R包中提供了有效使用这些模型的工具，可以在其他应用程序中使用。该方法被用来检查上下文依赖的突变，因为人类和黑猩猩的共同祖先。
Although the rates at which positions in the genome mutate are known to depend not only on the nucleotide to be mutated, but also on neighboring nucleotides, it remains challenging to do phylogenetic inference using models of context-dependent mutation. In these models, the effects of one mutation may in principle propagate to faraway locations, making it difficult to compute exact likelihoods. This article shows how to use bounds on the propagation of dependency to compute likelihoods of mutation of a given segment of genome by marginalizing over sufficiently long flanking sequence. This can be used for maximum likelihood or Bayesian inference. Protocols examining residuals and iterative model refinement are also discussed. Tools for efficiently working with these models are provided in an R package, which could be used in other applications. The method is used to examine context dependence of mutations since the common ancestor of humans and chimpanzee.