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The estimation of relative site variability among aligned homologous protein sequences

机译:对齐的同源蛋白序列之间的相对位点变异性的估计

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摘要

Maximum likelihood-based methods to estimate site by site substitution rate variability in aligned homologous protein sequences rely on the formulation of a phylogenetic tree and generally assume that the patterns of relative variability follow a pre-determined distribution. We present a phylogenetic tree-independent method of to estimate the relative variability of individual sites within large datasets of homologous protein sequences. It is based upon two simple assumptions. Firstly that substitutions observed between two closely related sequences are likely, in general, to occur at the most variable sites. Secondly that non-conservative amino acid substitutions tend to occur at more variable sites. Our methodology makes no assumptions regarding the underlying pattern of relative variability between sites. We have compared, using data simulated under a non-gamma distributed model, the performance of this approach to that of a maximum likelihood method that assumes gamma distributed rates. At low mean rates of evolution our method inferred site by site relative substitution rates more accurately than the maximum likelihood approach in the absence of prior assumptions about the relationships between sequences. Our method does not directly account for the effects of mutational saturation, However, we have incorporated an 'ad-hoc' modification than allows the accurate estimation of relative site variability in fast evolving and saturated datasets.
机译:基于最大似然性的方法来估计比对的同源蛋白质序列中的逐位取代率变异性,这依赖于系统发育树的表述,并且通常假设相对变异性的模式遵循预定的分布。我们提出了一种系统发育树无关的方法来估计同源蛋白序列的大型数据集中的单个站点的相对变异性。它基于两个简单的假设。首先,在两个紧密相关的序列之间观察到的取代通常可能发生在变化最大的位点。其次,非保守氨基酸取代倾向于发生在更多可变位点。我们的方法没有假设站点之间相对变异的潜在模式。我们使用在非伽玛分布模型下模拟的数据,将该方法的性能与假定伽玛分布速率的最大似然方法的性能进行了比较。在没有关于序列之间关系的先前假设的情况下,在低平均进化速率下,我们的方法比最大似然方法更准确地推导了逐位相对取代率。我们的方法没有直接考虑突变饱和的影响,但是,我们结合了“临时”修改,而不是允许快速估计和快速演化的饱和数据集中准确估计相对位点变异性。

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