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首页> 外文期刊>Molecular biology and evolution >The Branch-Site Test of Positive Selection Is Surprisingly Robust but Lacks Power under Synonymous Substitution Saturation and Variation in GC
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The Branch-Site Test of Positive Selection Is Surprisingly Robust but Lacks Power under Synonymous Substitution Saturation and Variation in GC

机译:正选择的分支站点测试出奇地强大,但是在同义置换饱和和GC中的变化下缺乏能力

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Positive selection is widely estimated from protein coding sequence alignments by the nonsynonymous-to-synonymous ratio co. Increasingly elaborate codon models are used in a likelihood framework for this estimation. Although there is widespread concern about the robustness of the estimation of the co ratio, more efforts are needed to estimate this robustness, especially in the context of complex models. Here, we focused on the branch-site codon model. We investigated its robustness on a large set ofsimulated data. First, we investigated the impact of sequence divergence. We found evidence of underestimation of the synonymous substitution rate for values as small as 0.5, with a slight increase in false positives for the branch-site test. When dS increases further, underestimation of dS is worse, but false positives decrease. Interestingly, the detection of true positives follows a similar distribution, with a maximum for intermediary values of dS. Thus, high dS is more of a concern for a loss of power (false negatives) than for false positives of the test. Second, we investigated the impact of GC content. We showed that there is no significant difference of false positives between high GC (up to ~80%) and low GC (~30%) genes. Moreover, neither shifts of GC content on a specific branch nor major shifts in GC along the gene sequence generate many false positives. Our results confirm that the branch-site is a very conservative test.
机译:从蛋白编码序列比对通过非同义与同义比率co广泛估计了阳性选择。越来越复杂的密码子模型被用于这种估计的可能性框架中。尽管人们普遍担心共比率估计的鲁棒性,但仍需要更多的努力来估计这种鲁棒性,尤其是在复杂模型的情况下。在这里,我们集中于分支站点密码子模型。我们在大量模拟数据上研究了其稳健性。首先,我们研究了序列发散的影响。我们发现,低至0.5的值被低估了同义替换率,分支站点测试的假阳性率略有增加。当dS进一步增加时,dS的低估会更严重,但误报率会降低。有趣的是,真实阳性的检测遵循相似的分布,中间值为dS最大值。因此,与测试的误报相比,高dS更值得关注的是功率损失(误报)。其次,我们调查了GC含量的影响。我们表明,高GC(高达〜80%)和低GC(〜30%)基因之间假阳性没有显着差异。此外,GC含量在特定分支上的变化或沿基因序列的GC的重大变化都不会产生许多假阳性。我们的结果证实分支站点是一个非常保守的测试。

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