Insights into the influence of priors in posterior mapping of discrete morphological characters: a case study in Annonaceae.
Insights into the influence of priors in posterior mapping of discrete morphological characters: a case study in Annonaceae.
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DOI：
10.1371/journal.pone.0010473
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发表时间：
2010-05-10
期刊：
影响因子：
3.7
通讯作者：
Chatrou LW
中科院分区：
文献类型：
--
作者：
Couvreur TL;Gort G;Richardson JE;Sosef MS;Chatrou LW
后验映射是一种越来越流行的基于贝叶斯的分层方法，用于推断性状历史和重建分子遗传学节点处的祖先状态，特别是形态性状。对于所有的贝叶斯分析来说，先验值的确定是分析中一个重要的组成部分。我们提供了一个例子，说明备选的先验选择如何严重影响结果和误导解释。对于两个对比离散的形态特征，即一个缓慢和一个快速发展的字符中发现的植物科番荔枝，我们指定了共8个不同的先验分布每个字符。我们研究了这些先验设置如何影响重要的汇总统计量。我们的分析表明，不同的先验分布有显着的影响的结果方面的平均数量的字符状态的变化。这些差异的出现是因为先验在确定模拟值将从参数空间的哪些区域中提取时起着至关重要的作用，而与手头的数据无关。然而，先验似乎更好地拟合数据，如果它们会导致更均匀的参数空间采样（正态后验分布），在这种情况下，替代标准差值对结果的影响很小。每个字符的最可能字符历史受到先验的不同影响。对于进化较慢的字符，相同的字符历史总是具有最高的后验概率，与所使用的先验无关。相比之下，快速发展的字符显示不同的最可能的字符历史取决于先验。这些差异可能与各性状的同质性水平有关。虽然我们的分析仅限于一个家庭内的两个形态特征，我们的研究结果强调了仔细选择先验值后映射的重要性。当以有意义的方式解释结果时，事先说明至关重要。如果没有更详细的研究，很难提出一个统计上合理的方法来进行事先规范。同时，我们建议，数据可以用来估计先验值的伽玛分布放置在后验映射的转换率。
Posterior mapping is an increasingly popular hierarchical Bayesian based method used to infer character histories and reconstruct ancestral states at nodes of molecular phylogenies, notably of morphological characters. As for all Bayesian analyses specification of prior values is an integrative and important part of the analysis. He we provide an example of how alternative prior choices can seriously influence results and mislead interpretations. For two contrasting discrete morphological characters, namely a slow and a fast evolving character found in the plant family Annonaceae, we specified a total of eight different prior distributions per character. We investigated how these prior settings affected important summary statistics. Our analyses showed that the different prior distributions had marked effects on the results in terms of average number of character state changes. These differences arise because priors play a crucial role in determining which areas of parameter space the values of the simulation will be drawn from, independent of the data at hand. However, priors seemed to fit the data better if they would result in a more even sampling of parameter space (normal posterior distribution), in which case alternative standard deviation values had little effect on the results. The most probable character history for each character was affected differently by the prior. For the slower evolving character, the same character history always had the highest posterior probability independent of the priors used. In contrast, the faster evolving character showed different most probable character histories depending on the prior. These differences could be related to the level of homoplasy exhibited by each character. Although our analyses were restricted to two morphological characters within a single family, our results underline the importance of carefully choosing prior values for posterior mapping. Prior specification will be of crucial importance when interpreting the results in a meaningful way. It is hard to suggest a statistically sound method for prior specification without more detailed studies. Meanwhile, we propose that the data could be used to estimate the prior value of the gamma distribution placed on the transformation rate in posterior mapping.
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