Linear Discriminant Analysis-Based Estimation of the False Discovery Rate for Phosphopeptide Identifications†

摘要: The development of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has made it possible to characterize phosphopeptides in an increasingly large-scale and high-throughput fashion. However, extracting confident phosphopeptide identifications from the resulting large data sets a similar fashion remains difficult, as does rigorously estimating false discovery rate (FDR) set identifications. This article describes analysis pipeline designed address these issues. first step is reanalyze that contain ambiguous assignments for incorporated phosphate(s) determine most likely arrangement phosphate(s). next employ expectation maximization algorithm estimate joint distribution peptide scores. A linear discriminant then performed how optimally combine scores (in this case, SEQUEST) into score possesses maximum discriminating power. Based on score, p- q-values each identification are calculated, FDR estimated. approach was applied study irradiated human skin fibroblasts provide robust phosphopeptides. Phosphopeptide Estimator software freely available download at http://ncrr.pnl.gov/software/.