Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 백은옥 | - |
dc.date.accessioned | 2019-11-26T04:44:44Z | - |
dc.date.available | 2019-11-26T04:44:44Z | - |
dc.date.issued | 2017-06 | - |
dc.identifier.citation | JOURNAL OF PROTEOME RESEARCH, v. 16, no. 6, page. 2231-2239 | en_US |
dc.identifier.issn | 1535-3893 | - |
dc.identifier.issn | 1535-3907 | - |
dc.identifier.uri | https://pubs.acs.org/doi/10.1021/acs.jproteome.7b00033 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/114530 | - |
dc.description.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. | en_US |
dc.description.sponsorship | We thank David Shteynberg at Institute for Systems Biology for providing us with a version of PeptideProphet compatible with MS-GF+. This work was supported by the National Research Foundation of Korea (NRF-2012M3A9B9036676, NRF-2014RIA2A1A11054147, NRF-2012M3A9D1054452, NRF-2012M3A9D1054705) and the Brain Korea 21 Plus Project. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | AMER CHEMICAL SOC | en_US |
dc.subject | proteogenomic search | en_US |
dc.subject | novel peptide identification | en_US |
dc.subject | spike-in data | en_US |
dc.subject | simulation | en_US |
dc.subject | false discovery rate control | en_US |
dc.title | Systematic Comparison of False-Discovery-Rate-Controlling Strategies for Proteogenomic Search Using Spike-in Experiments | en_US |
dc.type | Article | en_US |
dc.relation.no | 6 | - |
dc.relation.volume | 16 | - |
dc.identifier.doi | 10.1021/acs.jproteome.7b00033 | - |
dc.relation.page | 2231-2239 | - |
dc.relation.journal | JOURNAL OF PROTEOME RESEARCH | - |
dc.contributor.googleauthor | Li, Honglan | - |
dc.contributor.googleauthor | Park, Jonghun | - |
dc.contributor.googleauthor | Kim, Hyunwoo | - |
dc.contributor.googleauthor | Hwang, Kyu-Baek | - |
dc.contributor.googleauthor | Paek, Eunok | - |
dc.relation.code | 2017001665 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF COMPUTER SCIENCE | - |
dc.identifier.pid | eunokpaek | - |
dc.identifier.orcid | http://orcid.org/0000-0003-3655-9749 | - |
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