Dynamic programming alignment accuracy
Dynamic programming alignment accuracy
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DOI：
10.1089/cmb.1998.5.493
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发表时间：
1998-09-01
影响因子：
1.7
通讯作者：
Durbin, R
中科院分区：
文献类型：
--
作者：
Holmes, I;Durbin, R
当涉及到所产生的比对的准确性时，用于生成生物序列比对的算法具有固有的统计局限性。通过模拟，我们测量了标准全局动态规划方法的准确性，并表明可以通过“边缘漂移”近似对间隙附近正确路径周围的最佳得分路径的分布进行合理建模。我们还给出了一个表格，从中可以预测常用评分方案和序列分歧（PAM 和 BLOSUM 系列）的准确度值。最后，我们描述了如何计算给定比对的预期准确度，并展示了如何使用它来构建最佳准确度比对算法，该算法在模拟实验中生成比标准动态规划方法更准确的比对。
Algorithms for generating alignments of biological sequences have inherent statistical limitations when it comes to the accuracy of the alignments they produce. Using simulations, we measure the accuracy of the standard global dynamic programming method and show that it can be reasonably well modelled by an "edge wander" approximation to the distribution of the optimal scoring path around the correct path in the vicinity of a gap. We also give a table from which accuracy values can be predicted for commonly used scoring schemes and sequence divergences (the PAM and BLOSUM series), Finally we describe how to calculate the expected accuracy of a given alignment, and show how this can be used to construct an optimal accuracy alignment algorithm which generates significantly more accurate alignments than standard dynamic programming methods in simulated experiments.