STATISTICS OF SEQUENCE COMPARISON

这个项目是对一些问题的持续研究，这些问题是关于当比较两个蛋白质或DNA序列时，预计会出现哪些纯粹偶然的相似之处。一个附属的和相关的问题涉及到评分系统的定义，该评分系统是区分具有生物意义的模式和偶然性相似之处的最佳方式。今年的工作包括：a)制定一种更准确的方法，在数据库搜索的情况下评估统计意义。BLAST程序系列中E值的分配取决于数据库序列的标准组成的使用。这可能导致涉及具有相似偏向组合物的序列的比对得到不适当的低E值。一种新的方法重新估计了每对序列的相关统计参数，这些序列产生了看似重要的比对。新的参数导致了具有统计意义的修正估计。这可能会对PSI-BLAST的输出产生重大影响，其中在一次迭代期间包含假阳性可能会破坏所有进一步的结果。B)实现用于提取局部比对分数的统计参数的最大似然估计的快速方法。对有间隙的局部比对的统计参数的估计非常耗时。要将比例参数估计到0.5%以内，需要从24,000个成对比较中获得最佳的局部比对分数，这需要在标准的当前工作站上花费两个多小时的CPU时间。最近，T.Hwa和他在UCSD的同事们的一些工作提出了一种估计相关参数的更快的方法，包括从当地的路线岛屿收集分数。这种方法将所需的计算时间减少了10到20倍。我已经实现了Hwa等人的修改版本。方法，并启动了协作计划。-对齐、统计、替补得分、差距得分、极值分布

This project is a continuing study of questions concerning what similarities can be expected to occur purely by chance when two protein or DNA sequences are compared. A subsidiary and related question concerns the definition of scoring systems that are optimal for distinguishing biologically meaningful patterns from chance similarities. Work this year includes: a) The development of a more accurate method to assess statistical significance in the context of a database search. The assignment of E-values in the BLAST family of programs has depended upon the use of a standard composition for database sequences. This can result in alignments involving sequences with similarly biased compositions receiving inappropriately low E- values. A new approach re-estimates the relevant statistical parameters for each pair of sequences that yield a seemingly significant alignment. The new parameters lead to a revised estimate of statistical significance. This can have a major effect on the output of PSI-BLAST, where the inclusion of a false positive during one iteration can corrupt all further results. b) The implementation of a fast method for extracting a maximum-likelihood estimate of statistical parameters for local alignment scores. The estimation of statistical parameters for gapped local alignments has been very time consuming. To estimate the scale parameter to within 0.5% has required optimal local alignment scores from 24,000 pair wise comparisons, requiring over two hours of cpu time on a standard current workstation. Recently, some work of T. Hwa and colleagues at UCSD has suggested a much faster way of estimating the relevant parameters, involving the collection of scores from local alignment islands. This method has reduced the computation time required by a factor of 10 to20. I have implemented a modified version of the Hwa et al. method, and initiated plans for collaboration. - alignments, statistics, substitution scores, gap scores, extreme value distribution