Systematic Comparison of False-Discovery-Rate-Controlling Strategies for Proteogenomic Search
- Title
- Systematic Comparison of False-Discovery-Rate-Controlling Strategies for Proteogenomic Search
- Other Titles
- 프로테오지노믹 검색을 위한 오류 발견율 조절 전략들의 체계적인 비교
- Author
- Jonghun Park
- Alternative Author(s)
- 박종훈
- Advisor(s)
- 백은옥
- Issue Date
- 2018-02
- Publisher
- 한양대학교
- Degree
- Master
- Abstract
- Proteogenomic searches are useful for novel peptide identification from tandem mass spectra. Usually, separate and multi-stage 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 the existence of identified novel peptides. We simulated a proteogenomic search using a controlled, spike-in proteomic dataset. After confirming that the results of the simulated proteogenomic search were similar to those of a real proteogenomic search using a human cell line dataset, we evaluated the performance of six FDR control methods—global, separate, and multi-stage FDR estimation, respectively coupled with a target-decoy search and a mixture model-based method—on novel peptide identification. The multi-stage 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.
- URI
- https://repository.hanyang.ac.kr/handle/20.500.11754/68630http://hanyang.dcollection.net/common/orgView/200000432212
- Appears in Collections:
- GRADUATE SCHOOL[S](대학원) > COMPUTER SCIENCE(컴퓨터·소프트웨어학과) > Theses (Master)
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