Frequency Spectrum Neutrality Tests: One for All and All for One
Frequency Spectrum Neutrality Tests: One for All and All for One
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DOI：
10.1534/genetics.109.104042
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发表时间：
2009-09-01
期刊：
影响因子：
3.3
通讯作者：
Achaz, Guillaume
中科院分区：
文献类型：
--
作者：
Achaz, Guillaume
基于频谱的中性测试（例如，Tajima's D或Fu和Li's F）通常被群体遗传学家用作常规测试，以评估标准中性模型在其数据集上的拟合优度。在这里，我表明，这些中性测试是一个通用模型，包括他们所有的具体情况。我说明了如何利用这个一般框架来设计新的更强大的测试，更好地检测标准模型的偏差。最后，我通过展示它如何支持乳糖酶人类基因中的选择假设，克服了确定偏差，证明了SNP数据框架的有用性。这里提出的框架为构建新的测试铺平了道路，这些测试针对标准模型的特定违规行为进行了优化，最终将有助于解开进化的场景。
Neutrality tests based on the frequency spectrum (e.g., Tajima's D or Fu and Li's F) are commonly used by population geneticists as routine tests to assess the goodness-of-fit of the standard neutral model on their data sets. Here, I show that these neutrality tests are specific instances of a general model that encompasses them all. I illustrate how this general framework can be taken advantage of to devise new more powerful tests that better detect deviations froth the standard model. Finally, I exemplify the usefulness of the framework on SNP data by showing how it supports the selection hypothesis in the lactase human gene by overcoming the ascertainment bias. The framework presented here paves the way for constructing novel tests optimized for specific violations of the standard model that ultimately will help to unravel scenarios of evolution.