A conditional likelihood is required to estimate the selection coefficient in ancient DNA
A conditional likelihood is required to estimate the selection coefficient in ancient DNA
复制标题
需要条件似然来估计古代 DNA 中的选择系数
作者：
A. Valleriani
等位基因频率的时间序列是确定遗传漂变背景下自然选择强度的一组有用且独特的数据。从技术上讲，选择系数是通过似然函数来估计的，该似然函数是在假设可用轨迹跨越适应度景观的足够大的部分的情况下构建的。然而，特别是对于古老的DNA，通常只有一个这样的轨迹是可用的，并且健身景观的覆盖范围非常有限。事实上，一个单一的轨迹更能代表一个在初始和最终条件下都有条件的过程，而不是一个自由访问可用健身景观的过程。基于两个模型的人口遗传学，在这里，我们展示了如何建立一个选择系数的似然函数，考虑到统计特性的单一轨迹。我们发现，这种条件似然提供了一个精确的估计选择系数也当等位基因频率接近固定，而无条件的可能性失败。最后，我们讨论了这样一个事实，即传统的，无条件的可能性总是提供一个答案，这往往是不可证伪的，似乎也合理时，它是不正确的。
Time-series of allele frequencies are a useful and unique set of data to determine the strength of natural selection on the background of genetic drift. Technically, the selection coefficient is estimated by means of a likelihood function built under the hypothesis that the available trajectory spans a sufficiently large portion of the fitness landscape. Especially for ancient DNA, however, often only one single such trajectories is available and the coverage of the fitness landscape is very limited. In fact, one single trajectory is more representative of a process conditioned both in the initial and in the final condition than of a process free to visit the available fitness landscape. Based on two models of population genetics, here we show how to build a likelihood function for the selection coefficient that takes the statistical peculiarity of single trajectories into account. We show that this conditional likelihood delivers a precise estimate of the selection coefficient also when allele frequencies are close to fixation whereas the unconditioned likelihood fails. Finally, we discuss the fact that the traditional, unconditioned likelihood always delivers an answer, which is often unfalsifiable and appears reasonable also when it is not correct.