论文标题
在微生物组实验中对复杂的测量误差进行建模以估计相对丰度和检测效果
Modeling complex measurement error in microbiome experiments to estimate relative abundances and detection effects
论文作者
论文摘要
需要对微生物物种丰度进行准确的估计，以促进我们对微生物在人类和环境健康中所起的作用的理解。然而，人为构造的微生物组表明，微生物相对丰度的直观估计量是偏见的。为了解决这个问题，我们提出了一种半参数方法，以估计微生物组实验中的相对丰度，物种检测效应和/或跨样本污染。我们表明，某些实验设计导致可识别的模型参数，并且我们呈现一致的估计器和渐近有效的推理过程。值得注意的是，我们的过程可以估计单纯形边界上的相对丰度。我们证明了该方法比较实验方案，去除跨样本污染和估计物种可检测性的实用性。
Accurate estimates of microbial species abundances are needed to advance our understanding of the role that microbiomes play in human and environmental health. However, artificially constructed microbiomes demonstrate that intuitive estimators of microbial relative abundances are biased. To address this, we propose a semiparametric method to estimate relative abundances, species detection effects, and/or cross-sample contamination in microbiome experiments. We show that certain experimental designs result in identifiable model parameters, and we present consistent estimators and asymptotically valid inference procedures. Notably, our procedure can estimate relative abundances on the boundary of the simplex. We demonstrate the utility of the method for comparing experimental protocols, removing cross-sample contamination, and estimating species' detectability.
