Simple is beautiful: a straightforward approach to improve the delineation of true and false positives in PSI-BLAST searches
Simple is beautiful: a straightforward approach to improve the delineation of true and false positives in PSI-BLAST searches
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DOI：
10.1093/bioinformatics/btn130
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发表时间：
2008-06-01
期刊：
影响因子：
5.8
通讯作者：
Bundschuh, Ralf
中科院分区：
文献类型：
--
作者：
Lee, Marianne M.;Chan, Michael K.;Bundschuh, Ralf
动机：来自不同基因组计划的生物信息的泛滥和生物技术的快速发展使生物信息学工具成为现代生物学的一个组成部分。在广泛使用的序列比对工具中，BLAST和PSI-BLAST可以说是最流行的。PSI-BLAST，它使用一个迭代的配置文件的位置特异性得分矩阵（PSSM）为基础的搜索策略，是更敏感的比BLAST在检测弱同源性，从而使它适合于远程同源检测。PSI-BLAST的计算效率和高特异性得到了广泛的认可。然而，腐败的配置文件通过纳入假阳性sequences.Results的仍然是一个重大的挑战：我们已经开发出一个简单而优雅的方法来解决问题的PSI-BLAST搜索模型腐败。我们假设，将来自第一个（最少损坏）配置文件的结果与来自PSI-BLAST的稍后（最敏感）迭代的结果相结合，为真命中和假命中提供了更好的识别。因此，我们已经推导出一个公式，该公式利用来自这两个PSI-BLAST迭代的E值来获得用于对命中进行排序的品质因数。我们基于黄金标准测试集的验证结果表明，该品质因数确实比PSI-BLAST E值更好地描述了真阳性与假阳性。也许这一战略最值得注意的是，它的实施简单明了。
Motivation: The deluge of biological information from different genomic initiatives and the rapid advancement in biotechnologies have made bioinformatics tools an integral part of modern biology. Among the widely used sequence alignment tools, BLAST and PSI-BLAST are arguably the most popular. PSI-BLAST, which uses an iterative profile position specific score matrix (PSSM)-based search strategy, is more sensitive than BLAST in detecting weak homologies, thus making it suitable for remote homolog detection. Many refinements have been made to improve PSI-BLAST, and its computational efficiency and high specificity have been much touted. Nevertheless, corruption of its profile via the incorporation of false positive sequences remains a major challenge.Results: We have developed a simple and elegant approach to resolve the problem of model corruption in PSI-BLAST searches. We hypothesized that combining results from the first (least-corrupted) profile with results from later (most sensitive) iterations of PSI-BLAST provides a better discriminator for true and false hits. Accordingly, we have derived a formula that utilizes the E-values from these two PSI-BLAST iterations to obtain a figure of merit for rank-ordering the hits. Our verification results based on a gold-standard test set indicate that this figure of merit does indeed delineate true positives from false positives better than PSI-BLAST E-values. Perhaps what is most notable about this strategy is that it is simple and straightforward to implement.