Systematic Comparison of False-Discovery-Rate-Controlling Strategies for Proteogenomic Search Using Spike-in Experiments

作者：Li Honglan; Park Jonghun; Kim Hyunwoo; Hwang Kyu Baek^*; Paek Eunok^*

来源：Journal of Proteome Research, 2017, 16(6): 2231-2239.

DOI：10.1021/acs.jproteome.7b00033

• proteogenomic search
• novel peptide identification
• spike-in data
• simulation
• false discovery rate control

Proteogenoinit searches are useful for novel peptide identification from tandem mass spectra. Usually, separate and multistage approaches are adopted to accurately control the false discovery rate (FDR) for: proteogenomic search. Their performance on novel peptide identification has not been thoroughly evaluated; however, mainly due to the. difficulty in Confirming existence of identified novel peptides.' We, simulated a proteogenomic search controlled, spike-in proteomic data set. After confirming that the results of the simulated proteogenomic search were similar to those of a real proteogenomic search using,a human cell line data set, we evaluated the performance of six FDR Control methods-global, separate, and multistage FDR estimation) respectively, coupled to a target-decoy search and a mixture model-based: method on novel peptide identification. The multistage approach showed the highest accuracy for FDR. estimation. However, global and separate FDR estimation with the mixture model-based method showed higher sensitivities than others at the same true FDR. Furthermore, the mixture model based method performed equally well when applied without or with a reduced set of decoy sequences: Considering different prior probabilities for novel and known protein identification, we recommend using mixture model-based methods with separate FDR estimation for sensitive and reliable identification of novel peptides from proteogenomic searches.

• 出版日期2017-6