Institute of Electrical, Electronic and Bioengineering (IEBE), University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria.
J Proteome Res. 2010 May 7;9(5):2265-77. doi: 10.1021/pr901023v.
The target-decoy search strategy has been successfully applied in shotgun proteomics for validating peptide and protein identifications. If, on one hand, this method has proven to be very efficient for error estimation, on the other hand, little attention has been paid to the resulting sensitivity. Only two scores are normally used and thresholds are explored in a very simplistic way. In this work, a multivariate decoy analysis is described, where many quality parameters are considered. This analysis is treated in our approach as an optimization problem for sensitivity maximization. Furthermore, an efficient heuristic is proposed to solve this problem. Experiments comparing our method, termed MUDE (multivariate decoy database analysis), with traditional bivariate decoy analysis and with Peptide/ProteinProphet showed that our procedure significantly enhances the retrieved number of identifications when comparing the same false discovery rates. Particularly for phosphopeptide/protein identifications, we could demonstrate more than a two-fold increase in sensitivity compared with the Trans-Proteomic Pipeline tools.
靶标-诱饵搜索策略已成功应用于鸟枪法蛋白质组学中，用于验证肽和蛋白质的鉴定。一方面，该方法已被证明在误差估计方面非常有效，另一方面，对所得的灵敏度却关注甚少。通常仅使用两个分数，并且非常简单地探索阈值。在这项工作中，描述了一种多元诱饵分析，其中考虑了许多质量参数。在我们的方法中，该分析被视为用于最大灵敏度的优化问题。此外，还提出了一种有效的启发式算法来解决这个问题。与传统的双变量诱饵分析和 Peptide/ProteinProphet 进行的实验比较表明，当比较相同的假发现率时，我们的方法（称为 MUDE（多元诱饵数据库分析））显著提高了检索到的鉴定数量。特别是对于磷酸肽/蛋白质鉴定，与 Trans-Proteomic Pipeline 工具相比，我们能够证明灵敏度提高了两倍以上。
