Are skyline plot-based demographic estimates overly dependent on smoothing prior assumptions?
Are skyline plot-based demographic estimates overly dependent on smoothing prior assumptions?
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基于天际线图的人口统计估计是否过度依赖于平滑先前的假设？
DOI：
10.1101/2020.01.27.920215
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Parag K
中科院分区：
文献类型：
--
作者：
Parag K
在贝叶斯遗传学中，结合过程提供了一个信息框架，用于从从该群体中采样的序列的同源性（或树）推断该群体的有效大小的变化。流行的联合推断方法，如贝叶斯天际线图，Skyride和Skygridall模型这些人口规模的变化与一个不连续的，分段常数函数，但然后应用平滑之前，以确保他们的后验人口规模估计过渡逐渐随着时间的推移。这些先验分布隐含地编码了从所观察到的聚结数据或树中不可用的额外的群体大小信息。在这里，我们提出了一种新的统计，量化和分解的合并数据和先验假设的相对贡献所产生的后验估计精度。我们的统计还测量了由这些先验引入的额外的互信息。使用我们表明，因为它是令人惊讶的容易overparametrize分段常数人口模型，常见的平滑先验可能会导致过度自信和潜在的误导性推断，即使在稳健的实验设计。我们proposeas一个有用的工具，检测有效的人口规模估计是过度依赖于事先的假设，并改善量化的不确定性，在这些估计。[聚结过程;有效种群大小;信息论;随机动态;先验假设;天际线图。]
In Bayesian phylogenetics, the coalescent process provides an informative framework for inferring changes in the effective size of a population from a phylogeny (or tree) of sequences sampled from that population. Popular coalescent inference approaches such as theBayesian Skyline Plot,Skyride,andSkygridall model these population size changes with a discontinuous, piecewise-constant function but then apply a smoothing prior to ensure that their posterior population size estimates transition gradually with time. These prior distributions implicitly encode extra population size information that is not available from the observed coalescent data or tree. Here, we present a novel statistic,, to quantify and disaggregate the relative contributions of the coalescent data and prior assumptions to the resulting posterior estimate precision. Our statistic also measures the additional mutual information introduced by such priors. Usingwe show that, because it is surprisingly easy to overparametrize piecewise-constant population models, common smoothing priors can lead to overconfident and potentially misleading inference, even under robust experimental designs. We proposeas a useful tool for detecting when effective population size estimates are overly reliant on prior assumptions and for improving quantification of the uncertainty in those estimates.[Coalescent processes; effective population size; information theory; phylodynamics; prior assumptions; skyline plots.]