pValid: Validation Beyond the Target-Decoy Approach for Peptide Identification in Shotgun Proteomics
文献类型：期刊论文
| 作者 | Chi, Hao1,2; Zhang, Kun1,2; Zeng, Wen-Feng1,2; Yang, Hao1,2; Zhou, Wen-Jing1,2; He, Si-Min1,2 |
| 刊名 | JOURNAL OF PROTEOME RESEARCH
 |
| 出版日期 | 2019-07-01 |
| 卷号 | 18期号:7页码:2747-2758 |
| 关键词 | tandem mass spectrometry target-decoy approach validation methods false-positive rate false-negative rate |
| ISSN号 | 1535-3893 |
| DOI | 10.1021/acs.jproteome.8b00993 |
| 英文摘要 | As the de facto validation method in mass spectrometry-based proteomics, the target-decoy approach determines a threshold to estimate the false discovery rate and then filters those identifications beyond the threshold. However, the incorrect identifications within the threshold are still unknown and further validation methods are needed. In this study, we characterized a framework of validation and investigated a number of common and novel validation methods. We first defined the accuracy of a validation method by its false-positive rate (FPR) and false-negative rate (FNR) and, further, proved that a validation method with lower FPR and FNR led to identifications with higher sensitivity and precision. Then we proposed a validation method named pValid that incorporated an open database search and a theoretical spectrum prediction strategy via a machine-learning technology. pValid was compared with four common validation methods as well as a synthetic peptide validation method. Tests on three benchmark data sets indicated that pValid had an FPR of 0.03% and an FNR of 1.79% on average, both superior to the other four common validation methods. Tests on a synthetic peptide data set also indicated that the FPR and FNR of pValid were better than those of the synthetic peptide validation method. Tests on a large-scale human proteome data set indicated that pValid successfully flagged the highest number of incorrect identifications among all five methods. Further considering its cost-effectiveness, pValid has the potential to be a feasible validation tool for peptide identification. |
| 资助项目 | National Key Research and Development Program of China[2016YFA0501300] ; CAS Interdisciplinary Innovation Team[Y604061000] ; National Natural Science Foundation of China[21475141] ; Youth Innovation Promotion Association CAS[2014091] |
| WOS研究方向 | Biochemistry & Molecular Biology |
| 语种 | 英语 |
| WOS记录号 | WOS:000474795500006 |
| 出版者 | AMER CHEMICAL SOC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/4319]  |
| 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; He, Si-Min |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chi, Hao,Zhang, Kun,Zeng, Wen-Feng,et al. pValid: Validation Beyond the Target-Decoy Approach for Peptide Identification in Shotgun Proteomics[J]. JOURNAL OF PROTEOME RESEARCH,2019,18(7):2747-2758. |
| APA | Chi, Hao,Zhang, Kun,Zeng, Wen-Feng,Yang, Hao,Zhou, Wen-Jing,&He, Si-Min.(2019).pValid: Validation Beyond the Target-Decoy Approach for Peptide Identification in Shotgun Proteomics.JOURNAL OF PROTEOME RESEARCH,18(7),2747-2758. |
| MLA | Chi, Hao,et al."pValid: Validation Beyond the Target-Decoy Approach for Peptide Identification in Shotgun Proteomics".JOURNAL OF PROTEOME RESEARCH 18.7(2019):2747-2758. |
入库方式： OAI收割
来源：计算技术研究所
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