ESTIMATING THE GUMBEL SCALE PARAMETER FOR LOCAL ALIGNMENT OF RANDOM SEQUENCES BY IMPORTANCE SAMPLING WITH STOPPING TIMES.
ESTIMATING THE GUMBEL SCALE PARAMETER FOR LOCAL ALIGNMENT OF RANDOM SEQUENCES BY IMPORTANCE SAMPLING WITH STOPPING TIMES.
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DOI：
10.1214/08-aos663
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发表时间：
2009-12-01
影响因子：
4.5
通讯作者：
Spouge JL
中科院分区：
文献类型：
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作者：
Park Y;Sheetlin S;Spouge JL
两个随机序列的缺口局部比对得分服从Gumbel分布。如果计算机可以在一秒内估计出甘贝尔分布的参数，使用任意的比对评分方案可能会增加在网络上搜索生物序列数据库的敏感性。在此基础上，给出了相应的冈贝尔分布尺度参数的新公式。我们推测这个方程是精确的，尽管目前的数字证据是有限的。该方程涉及随机序列的全局比对中的上升阶梯变量。在全局比对模拟中，梯形变量产生指定随机序列长度的停止时间。由于随机长度，以及我们的重要抽样的试验分布发生在与我们的目标分布不同的样本空间，我们的研究得到了映射定理，这自然地导致了一个有效的动态规划算法来确定重要抽样的权重。然后，使用几种流行的比对评分方案进行的数值研究检验了所产生的模拟的效率和准确性。
The gapped local alignment score of two random sequences follows a Gumbel distribution. If computers could estimate the parameters of the Gumbel distribution within one second, the use of arbitrary alignment scoring schemes could increase the sensitivity of searching biological sequence databases over the web. Accordingly, this article gives a novel equation for the scale parameter of the relevant Gumbel distribution. We speculate that the equation is exact, although present numerical evidence is limited. The equation involves ascending ladder variates in the global alignment of random sequences. In global alignment simulations, the ladder variates yield stopping times specifying random sequence lengths. Because of the random lengths, and because our trial distribution for importance sampling occurs on a different sample space from our target distribution, our study led to a mapping theorem, which led naturally in turn to an efficient dynamic programming algorithm for the importance sampling weights. Numerical studies using several popular alignment scoring schemes then examined the efficiency and accuracy of the resulting simulations.