观测延迟会偏倚进化竞争中选择优势的推断
Observation delays can bias inference of selective advantage in evolutionary competition
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中文总结 AI 辅助
本文以英国SARS-CoV-2变异株替代为实证，通过两类型模型研究发现，观测延迟会偏倚非线性进化竞争中logit斜率推断的相对生长优势，需将其纳入考量。
中文摘要 AI 辅助
相对频率轨迹常被用于推断竞争生物种群的选择优势，一种常见的实证方法是对入侵类型经logit变换后的频率拟合线性函数，并将斜率解读为相对优势。本文测试了当竞争类型存在类型特异性观测延迟时，该估计器会受到何种影响。我们以英国的SARS-CoV-2变异株替代作为实证动机，采用简单的两类型模型研究该机制。在理想指数替代模型中，若延迟计数在形成频率前已聚合且无边界效应，固定或随机分布的观测延迟会改变观测到的log-odds轨迹的截距，但不改变其斜率；在相对增长随时间变化的非线性SIR型模型中，延迟会使竞争变异株在不同动力学阶段进行比较，从而显著偏倚拟合的logit斜率，即便延迟替代轨迹在logit尺度上仍近乎线性，这种偏倚也会发生。因此，对观测数据的良好logistic拟合不足以保证推断的logit斜率能很好地近似相对增长优势，当将logit斜率作为非线性进化竞争中相对适合度的替代指标时，应考虑观测延迟的影响。
英文摘要
Relative-frequency trajectories are often used to infer selective advantage in competing biological populations. A common empirical approach is to fit a linear function to the logit-transformed frequency of an invading type and interpret the slope as the relative advantage. Here we test how this estimator is affected when the competing types are observed after type-specific delays. We use SARS-CoV-2 variant replacement in the United Kingdom as empirical motivation and study the mechanism with simple two-type models. In an ideal exponential replacement model, fixed or randomly distributed observation delays change the intercept of the observed log-odds trajectory but not its slope, provided that delayed counts are aggregated before frequencies are formed and boundary effects are absent. In nonlinear SIR-type models, where the relative growth is time-dependent, delays can compare the competing variants at different dynamical phases and substantially bias the fitted logit slope. This bias can occur even when the delayed replacement trajectory remains nearly linear on the logit scale. Thus, a good logistic fit to the observed data is not sufficient to guarantee that the inferred logit slope approximates well the relative growth advantage. Observation delays should therefore be accounted for when logit slopes are used as proxies for relative fitness in nonlinear evolutionary competition.
发表机构
- Faculty of Mathematics, Physics, and Informatics（数学、物理与信息学院）
- Comenius University（布拉迪斯拉发康斯坦丁尼乌斯大学）
机构由 AI 辅助整理，请以论文原文为准。
