Estimating transmission from genetic and epidemiological data: a metric to compare transmission trees
Estimating transmission from genetic and epidemiological data: a metric to compare transmission trees
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根据遗传和流行病学数据估计传播：比较传播树的指标
DOI：
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发表时间：
2016
期刊：
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通讯作者：
C. Colijn
中科院分区：
文献类型：
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作者：
M. Kendall;D. Ayabina;C. Colijn
重建谁感染了谁是分析流行病学数据的一个核心挑战。最近，测序技术的进步导致人们对贝叶斯方法越来越感兴趣，该方法使用病原体的遗传数据来推断谁感染了谁。这种方法背后的逻辑是，基因上几乎相同的分离株比那些非常不同的分离株更有可能是最近传播的。已经开发了许多方法来执行此推断。然而，测试它们的收敛性，检查后验集的传输树和比较方法的性能是挑战的事实，推理的对象-传输树-是一个复杂的离散结构。我们引入一个度量传输树来量化它们之间的距离。该指标可以适应具有未采样个体的树，并突出显示源病例和每个感染者感染数量的差异。我们在简单的模拟场景和结核病爆发的后验传播树上说明了它的性能。我们发现，该度量揭示了后验对先验的敏感性，以及树的集合由不同的簇组成。我们使用的度量来定义中位数树总结这些集群。随着这一领域的不断成熟，将需要量化工具来比较传输树，以评估MCMC收敛性，探索后验树并对各种方法进行基准测试。
Reconstructing who infected whom is a central challenge in analysing epidemiological data. Recently, advances in sequencing technology have led to increasing interest in Bayesian approaches to inferring who infected whom using genetic data from pathogens. The logic behind such approaches is that isolates that are nearly genetically identical are more likely to have been recently transmitted than those that are very different. A number of methods have been developed to perform this inference. However, testing their convergence, examining posterior sets of transmission trees and comparing methods' performance are challenged by the fact that the object of inference - the transmission tree - is a complicated discrete structure. We introduce a metric on transmission trees to quantify distances between them. The metric can accommodate trees with unsampled individuals, and highlights differences in the source case and in the number of infections per infector. We illustrate its performance on simple simulated scenarios and on posterior transmission trees from a TB outbreak. We find that the metric reveals where the posterior is sensitive to the priors, and where collections of trees are composed of distinct clusters. We use the metric to define median trees summarising these clusters. Quantitative tools to compare transmission trees to each other will be required for assessing MCMC convergence, exploring posterior trees and benchmarking diverse methods as this field continues to mature.