原理性、实用性、灵活性、快速性：系统发育因子分析的新方法
Principled, practical, flexible, fast: a new approach to phylogenetic factor analysis
摘要：
生物表型是复杂进化过程的产物，其中选择力以未知的方式影响多个生物性状测量。系统发生因子分析在一组生物的进化历史中解开这些关系。科学家寻求采用这种建模框架面临着许多建模和实施决策，其中的细节构成计算和可复制性的挑战。一般和有影响力的社区就业需要一个数据科学分析计划，平衡灵活性，速度和易用性，同时最大限度地减少模型和算法调整。即使在存在非平凡的系统发育模型的约束，我们表明，可以分析解决潜在的因素的不确定性的方式，（a）艾滋病模型的灵活性，（b）加速计算（多达500倍）和（c）减少所需的调整。我们进一步提出了实用的指导推理和建模决策，以及诊断和解决这些分析中的常见问题。我们在一个自动化的管道中编纂了这个分析计划，该管道将潜在的大量建模决策提炼成一小部分（通常是二进制）选择。我们证明了这些方法和分析计划在不同规模的四个现实世界中的问题的效用。
英文摘要：
Biological phenotypes are products of complex evolutionary processes in which selective forces influence multiple biological trait measurements in unknown ways. Phylogenetic factor analysis disentangles these relationships across the evolutionary history of a group of organisms. Scientists seeking to employ this modeling framework confront numerous modeling and implementation decisions, the details of which pose computational and replicability challenges. General and impactful community employment requires a data scientific analysis plan that balances flexibility, speed and ease of use, while minimizing model and algorithm tuning. Even in the presence of non-trivial phylogenetic model constraints, we show that one may analytically address latent factor uncertainty in a way that (a) aids model flexibility, (b) accelerates computation (by as much as 500-fold) and (c) decreases required tuning. We further present practical guidance on inference and modeling decisions as well as diagnosing and solving common problems in these analyses. We codify this analysis plan in an automated pipeline that distills the potentially overwhelming array of modeling decisions into a small handful of (typically binary) choices. We demonstrate the utility of these methods and analysis plan in four real-world problems of varying scales.
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