Systematic Comparison of False-Discovery-Rate-Controlling Strategies for Proteogenomic Search Using Spike-in Experiments
- Authors
- Li, Honglan; Park, Jonghun; Kim, Hyunwoo; Hwang, Kyu-Baek; Paek, Eunok
- Issue Date
- Jun-2017
- Publisher
- AMER CHEMICAL SOC
- Keywords
- proteogenomic search; novel peptide identification; spike-in data; simulation; false discovery rate control
- Citation
- JOURNAL OF PROTEOME RESEARCH, v.16, no.6, pp.2231 - 2239
- Journal Title
- JOURNAL OF PROTEOME RESEARCH
- Volume
- 16
- Number
- 6
- Start Page
- 2231
- End Page
- 2239
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/6347
- DOI
- 10.1021/acs.jproteome.7b00033
- ISSN
- 1535-3893
- Abstract
- 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.
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