A Simple Derivation of the Distribution of Pairwise Local Protein Sequence Alignment Scores

O. Bastien
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引用次数: 8

Abstract

Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic data. In the asymptotic limit of long sequences, the Karlin-Altschul model computes a P-value assuming that the number of high scoring matching regions above a threshold is Poisson distributed. Using a simple approach combined with recent results in reliability theory, we demonstrate here that the Karlin-Altshul model can be derived with no reference to the extreme events theory. Sequences were considered as systems in which components are amino acids and having a high redundancy of Information reflected by their alignment scores. Evolution of the information shared between aligned components determined the Shared Amount of Information (SA.I.) between sequences, i.e. the score. The Gumbel distribution parameters of aligned sequences scores find here some theoretical rationale. The first is the Hazard Rate of the distribution of scores between residues and the second is the probability that two aligned residues do not lose bits of information (i.e. conserve an initial pairing score) when a mutation occurs.
两两局部蛋白质序列比对分数分布的简单推导
通过Blast或Smith-Waterman等各种方法获得的生物序列成对比对的可信度对于基因组数据的自动分析至关重要。在长序列的渐近极限下,Karlin-Altschul模型假设高于阈值的高分匹配区域的数量为泊松分布,计算p值。利用一种简单的方法结合可靠性理论的最新结果,我们在这里证明了可以在不参考极端事件理论的情况下导出Karlin-Altshul模型。序列被认为是一个系统,其中的成分是氨基酸,并具有高冗余的信息反映了他们的比对得分。序列间共享信息的演化决定了序列间共享信息量(SA.I),即得分。排列序列分数的Gumbel分布参数在这里找到了一些理论依据。第一个是残基之间分数分布的危险率,第二个是两个对齐残基在突变发生时不丢失信息位(即保留初始配对分数)的概率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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