Chronospaces: An R package for the statistical exploration of divergence times promotes the assessment of methodological sensitivity

IF 6.3 2区 环境科学与生态学 Q1 ECOLOGY
Nicolás Mongiardino Koch, Pablo Milla Carmona
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引用次数: 0

Abstract

Much of our understanding of the history of life hinges upon time calibration, the process of assigning absolute times to cladogenetic events. Bayesian approaches to time‐scaling phylogenetic trees have dramatically grown in complexity, and depend today upon numerous methodological choices. Arriving at objective justifications for all of these is difficult and time‐consuming. Thus, divergence times are routinely inferred under only one or a handful of parametric conditions, often times chosen arbitrarily. Progress towards building robust biological timescales necessitates the development of better methods to visualize and quantify the sensitivity of results to these decisions. Here, we present an R package that assists in this endeavour through the use of chronospaces, that is, graphical representations summarizing variation in the node ages contained in time‐calibrated trees. We further test this approach by estimating divergence times for three empirical datasets—spanning widely differing evolutionary timeframes—using the software PhyloBayes. Our results reveal large differences in the impact of many common methodological decisions, with the choice of clock (uncorrelated vs autocorrelated) and loci having strong effects on inferred ages. Other decisions have comparatively minor consequences, including the use of the computationally intensive site‐heterogeneous model CAT‐GTR, whose effect might only be discernible for exceedingly old divergences (e.g. the deepest eukaryote nodes). The package chronospace implements a range of graphical and analytical tools that assist in the exploration of sensitivity and the prioritization of computational resources in the inference of divergence times.
Chronospaces:用于统计探索分歧时间的 R 软件包,促进方法敏感性评估
我们对生命历史的理解在很大程度上取决于时间校准,即为系统发育事件分配绝对时间的过程。贝叶斯方法对系统发育树进行时间标定的复杂性急剧增加,如今依赖于众多的方法选择。为所有这些选择找到客观的理由既困难又耗时。因此,通常只能在一个或少数几个参数条件下推断分异时间,而这些条件往往是任意选择的。要在构建稳健的生物时间尺度方面取得进展,就必须开发更好的方法来直观地量化结果对这些决定的敏感性。在这里,我们提出了一个 R 软件包,通过使用时间空间(即总结时间校准树所含节点年龄变化的图形表示法)来协助这项工作。我们使用 PhyloBayes 软件估算了三个经验数据集的分歧时间,从而进一步检验了这种方法。我们的结果表明,许多常见的方法学决定对推断年龄的影响存在很大差异,时钟(不相关与自相关)和位点的选择对推断年龄有很大影响。其他决定的影响相对较小,包括使用计算密集的位点异构模型 CAT-GTR,其影响可能只在极古老的分化(如最深的真核生物节点)中才能发现。chronospace 软件包实现了一系列图形和分析工具,有助于在推断发散时间时探索敏感性和计算资源的优先级。
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来源期刊
CiteScore
11.60
自引率
3.00%
发文量
236
审稿时长
4-8 weeks
期刊介绍: A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas. MEE publishes methodological papers in any area of ecology and evolution, including: -Phylogenetic analysis -Statistical methods -Conservation & management -Theoretical methods -Practical methods, including lab and field -This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual. A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.
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