使用 Mascot Percolator 进行准确且灵敏的肽段鉴定。
Accurate and sensitive peptide identification with Mascot Percolator.
作者信息
Brosch Markus, Yu Lu, Hubbard Tim, Choudhary Jyoti
机构信息
The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom.
出版信息
J Proteome Res. 2009 Jun;8(6):3176-81. doi: 10.1021/pr800982s.
Abstract
Sound scoring methods for sequence database search algorithms such as Mascot and Sequest are essential for sensitive and accurate peptide and protein identifications from proteomic tandem mass spectrometry data. In this paper, we present a software package that interfaces Mascot with Percolator, a well performing machine learning method for rescoring database search results, and demonstrate it to be amenable for both low and high accuracy mass spectrometry data, outperforming all available Mascot scoring schemes as well as providing reliable significance measures. Mascot Percolator can be readily used as a stand alone tool or integrated into existing data analysis pipelines.
摘要
对于诸如Mascot和Sequest等序列数据库搜索算法而言，合理的评分方法对于从蛋白质组串联质谱数据中灵敏且准确地鉴定肽段和蛋白质至关重要。在本文中，我们展示了一个软件包，它将Mascot与Percolator（一种用于重新评估数据库搜索结果的性能良好的机器学习方法）相连接，并证明其适用于低精度和高精度质谱数据，其性能优于所有现有的Mascot评分方案，同时还能提供可靠的显著性度量。Mascot Percolator既可以直接作为独立工具使用，也可以集成到现有的数据分析流程中。
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