Evaluation of the Consensus of Four Peptide Identification Algorithms for Tandem Mass Spectrometry Based Proteomics.
Evaluation of the Consensus of Four Peptide Identification Algorithms for Tandem Mass Spectrometry Based Proteomics.
复制标题
DOI：
10.4172/jpb.1000119
复制
发表时间：
2010-02-05
期刊：
影响因子：
--
通讯作者：
Lyons-Weiler J
中科院分区：
文献类型：
--
作者：
Dagda RK;Sultana T;Lyons-Weiler J
蛋白质数据库搜索算法的不同评分方案和过滤设置的可用性极大地扩展了从质谱/质谱中识别候选肽的搜索方法的数量。我们之前已经表明，与使用单个搜索引擎（单个方法）相比，结合三种搜索算法的基于共识的方法产生更高的灵敏度和特异性。我们假设四个搜索引擎(Sequest, Mascot， X！Tandem和Phenyx)可进一步提高敏感性和特异性。生成ROC图来测量来自同一数据集的5460种共识方法的敏感性和特异性。我们发现Mascot在敏感性和特异性方面优于单个方法，而Phenyx表现最差。联合共识法的敏感性普遍较高，而交叉共识法的特异性较高。与使用三个搜索引擎的联合方法相比，四种搜索算法的联合方法略微提高了灵敏度，但没有提高特异性。这表明，基于特定搜索算法组合的策略，而不仅仅是“尽可能多的搜索引擎”，可能是肽识别成功的关键策略。最后，我们提供了针对不同用户特定条件优化MS/MS光谱中肽鉴定的敏感性或特异性的策略。
The availability of different scoring schemes and filter settings of protein database search algorithms has greatly expanded the number of search methods for identifying candidate peptides from MS/MS spectra. We have previously shown that consensus-based methods that combine three search algorithms yield higher sensitivity and specificity compared to the use of a single search engine (individual method). We hypothesized that union of four search engines (Sequest, Mascot, X!Tandem and Phenyx) can further enhance sensitivity and specificity. ROC plots were generated to measure the sensitivity and specificity of 5460 consensus methods derived from the same dataset. We found that Mascot outperformed individual methods for sensitivity and specificity, while Phenyx performed the worst. The union consensus methods generally produced much higher sensitivity, while the intersection consensus methods gave much higher specificity. The union methods from four search algorithms modestly improved sensitivity, but not specificity, compared to union methods that used three search engines. This suggests that a strategy based on specific combination of search algorithms, instead of merely ‘as many search engines as possible’, may be key strategy for success with peptide identification. Lastly, we provide strategies for optimizing sensitivity or specificity of peptide identification in MS/MS spectra for different user-specific conditions.