pValid 2: A deep learning based validation method for peptide identification in shotgun proteomics with increased discriminating power

doi:10.1016/j.jprot.2021.104414

	pValid 2: A deep learning based validation method for peptide identification in shotgun proteomics with increased discriminating power
	Zhou, Wen-Jing 1,2; Wei, Zhuo-Hong 1,2; He, Si-Min 1,2; Chi, Hao 1,2
	2022-01-16
发表期刊	JOURNAL OF PROTEOMICS
ISSN	1874-3919
卷号	251 页码:9
摘要	Tandem mass spectrometry has been the principal method in shotgun proteomics for peptide and protein identification. However, incorrect identifications reported by proteome search engines are still unknown, and further validation methods are needed. We have proposed a validation method pValid before, but its scope of application is limited because two features used in pValid are related to open database search and sub-optimal peptide candidates for tandem mass spectra, and the performance on complex datasets still has room for improvement. In this study, we developed a more comprehensive validation method, pValid 2, to break these limitations by removing the two features and bringing in a new feature related to the retention time predicted by a deep learning-based method pPredRT. pValid 2 yielded an average false positive rate of 0.03% and an average false negative rate of 1.37% on three testing datasets, better than those of pValid, and flagged 8.47% to 11.31% more incorrect identifications than pValid on two complex datasets. Moreover, pValid 2 flagged almost all decoy identifications in validating the open-search datasets. In addition, the function of validating identifications given by MaxQuant and MS-GF+ was implemented in pValid 2, and the validation results showed that pValid 2 performed dramatically better than three metabolic labeling validation methods. Further considering its costeffectiveness as a pure computational approach, pValid 2 has the potential to be a widely used validation tool for peptide identifications of any proteome search engines in shotgun proteomics. Significance: Identification results given by shotgun proteomics are vital to life science research. The correctness of identifications deeply affects the precision of the subsequent studies about protein structures and functions, protein-protein interactions, pathogenic mechanism, and targeted drugs. Thus, validating the correctness of identifications is crucial and urgent. In 2019, we developed an identification credibility validation method named pValid, whose false positive rate (FPR) is 0.03% and false negative rate (FNR) is 1.79%, comparable to those of the gold standard, i.e., the Synthetic-peptide validation method. However, pValid can only be used for validating the results from pFind, and its validation performance on a few complex datasets still has room for improvement. So, in this submission, we proposed pValid 2, a more comprehensive computational validation method that can validate identifications from any proteome search engines with increased discriminating power.
关键词	Proteomics Tandem mass spectrometry Retention time Validation method Deep learning
DOI	10.1016/j.jprot.2021.104414
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation of China[32022046] ; National Key Research and Development Program of China[2016YFA0501301]
WOS研究方向	Biochemistry & Molecular Biology
WOS类目	Biochemical Research Methods
WOS记录号	WOS:000721676300008
出版者	ELSEVIER
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/18128
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Chi, Hao
作者单位	1.Chinese Acad Sci, Inst Comp Technol, CAS, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Wen-Jing,Wei, Zhuo-Hong,He, Si-Min,et al. pValid 2: A deep learning based validation method for peptide identification in shotgun proteomics with increased discriminating power[J]. JOURNAL OF PROTEOMICS,2022,251:9.
APA	Zhou, Wen-Jing,Wei, Zhuo-Hong,He, Si-Min,&Chi, Hao.(2022).pValid 2: A deep learning based validation method for peptide identification in shotgun proteomics with increased discriminating power.JOURNAL OF PROTEOMICS,251,9.
MLA	Zhou, Wen-Jing,et al."pValid 2: A deep learning based validation method for peptide identification in shotgun proteomics with increased discriminating power".JOURNAL OF PROTEOMICS 251(2022):9.