download0 view154
twitter facebook

공공누리This item is licensed Korea Open Government License

Title
Systematic Comparison of False-Discovery-Rate-Controlling Strategies for Proteogenomic Search Using Spike-in Experiments
Author(s)
이홍란백은옥김현우박종훈황규백
Publication Year
2017-05-05
Abstract
Proteogenomic 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 hasnot been thoroughly evaluated, however, mainly due to the difficulty in confirming the existence of identified novel peptides. We simulated a proteogenomic search using a 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 modelbased 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.
Keyword
proteogenomic search; novel peptide identification; spike-in data; simulation; false discovery rate control
Journal Title
Journal of Proteome
Citation Volume
16
ISSN
1535-3893
Files in This Item:
There are no files associated with this item.
Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
URI
https://repository.kisti.re.kr/handle/10580/14604
http://www.ndsl.kr/ndsl/search/detail/article/articleSearchResultDetail.do?cn=NART77935074
Export
RIS (EndNote)
XLS (Excel)
XML

Browse