Control of the false discovery rate applied to the detection of positively selected amino acid sites
Control of the false discovery rate applied to the detection of positively selected amino acid sites
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DOI：
10.1093/molbev/msj095
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发表时间：
2006-05-01
影响因子：
10.7
通讯作者：
Rodrigo, A
中科院分区：
文献类型：
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作者：
Guindon, S;Black, M;Rodrigo, A
在这篇文章中，我们认为概率识别的氨基酸位置，积极的选择下演变为一个多重假设检验问题。在同源编码序列比对的每个密码子位点测试零假设“H（0，s）：位点s在负选择或中性进化过程下进化”。标准假设检验是基于对错误拒绝的零假设或I类错误率的预期比例的控制。然而，随着测试数量的增加，单个测试的功效可能变得不可接受地低。统计学的最新进展表明，假发现率在这种情况下，在那些估计在这种选择制度下进化的网站中，不进化的网站的预期比例是可以控制的。在显著结果中保持低的假阳性比例通常会导致功效的增加。在这篇文章中，我们表明，控制误检率是相关的搜索积极选择的网站。我们还比较了这种新的方法，传统的方法，使用广泛的模拟。
In this article, we consider the probabilistic identification of amino acid positions that evolve under positive selection as a multiple hypothesis testing problem. The null hypothesis "H(0,s): site s evolves under a negative selection or under a neutral process of evolution" is tested at each codon site of the alignment of homologous coding sequences. Standard hypothesis testing is based on the control of the expected proportion of falsely rejected null hypotheses or type-I error rate. As the number of tests increases, however, the power of an individual test may become unacceptably low. Recent advances in statistics have shown that the false discovery rate-in this case, the expected proportion of sites that do not evolve under positive selection among those that are estimated to evolve under this selection regime-is a quantity that can be controlled. Keeping the proportion of false positives low among the significant results generally leads to an increase in power. In this article, we show that controlling the false detection rate is relevant when searching for positively selected sites. We also compare this new approach to traditional methods using extensive simulations.