Understanding the improved sensitivity of spectral library searching over sequence database searching in proteomics data analysis

被引:64
|
作者
Zhang, Xin [1 ]
Li, Yunzi [1 ]
Shao, Wenguang [1 ]
Lam, Henry [1 ]
机构
[1] Hong Kong Univ Sci & Technol, Dept Chem & Biomol Engn, Clear Water Bay, Hong Kong, Peoples R China
关键词
Bioinformatics; Sequence searching; Spectral library; Spectral searching; INDUCED DISSOCIATION SPECTRA; PEPTIDE IDENTIFICATION; PROTEIN IDENTIFICATION; MS/MS SPECTRA; TANDEM; VALIDATION; PREDICTION; STRATEGY;
D O I
10.1002/pmic.201000492
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Spectral library searching has been recently proposed as an alternative to sequence database searching for peptide identification from MS/MS. We performed a systematic comparison between spectral library searching and sequence database searching using a wide variety of data to better demonstrate, and understand, the superior sensitivity of the former observed in preliminary studies. By decoupling the effect of search space, we demonstrated that the success of spectral library searching is primarily attributable to the use of real library spectra for matching, without which the sensitivity advantage largely disappears. We further determined the extent to which the use of real peak intensities and non-canonical fragments, both under-utilized information in sequence database searching, contributes to the sensitivity advantage. Lastly, we showed that spectral library searching is disproportionately more successful in identifying low-quality spectra, and complex spectra of higher- charged precursors, both important frontiers in peptide sequencing. Our results answered important outstanding questions about this promising yet unproven method using well-controlled computational experiments and sound statistical approaches.
引用
收藏
页码:1075 / 1085
页数:11
相关论文
共 40 条
  • [21] Integrating de novo sequencing with sequence database and spectral library search for in-depth analysis of DIA data with PEAKS
    Chen, Xin
    Chen, Clark
    Hopkins, Julia
    Shan, Paul
    MOLECULAR & CELLULAR PROTEOMICS, 2019, 18 (08) : S56 - S56
  • [22] Improved Data Mining by Using TPP-based Analysis Workflows for Searching MS/MS Data
    Quandt, A.
    Malstroem, L.
    Lam, H.
    Shteynberg, D.
    Aebersold, R.
    MOLECULAR & CELLULAR PROTEOMICS, 2009, : S24 - S24
  • [23] Protein analysis by mass spectrometry and sequence database searching: Tools for cancer research in the post-genomic era
    Gygi, SP
    Han, DKM
    Gingras, AC
    Sonenberg, N
    Aebersold, R
    ELECTROPHORESIS, 1999, 20 (02) : 310 - 319
  • [24] MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
    Steinegger, Martin
    Soeding, Johannes
    NATURE BIOTECHNOLOGY, 2017, 35 (11) : 1026 - 1028
  • [25] MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
    Martin Steinegger
    Johannes Söding
    Nature Biotechnology, 2017, 35 : 1026 - 1028
  • [26] Generalized method for probability-based peptide and protein identification from tandem mass Spectrometry data and sequence database searching
    Ramos-Fernandez, Antonio
    Paradela, Alberto
    Navajas, Rosana
    Albar, Juan Pablo
    MOLECULAR & CELLULAR PROTEOMICS, 2008, 7 (09) : 1748 - 1754
  • [27] Protein analysis by mass spectrometry and sequence database searching:: A proteomic approach to identify human lymphoblastoid cell line proteins
    Joubert-Caron, R
    Le Caër, JP
    Montandon, F
    Poirier, F
    Pontet, M
    Imam, N
    Feuillard, J
    Bladier, D
    Rossier, J
    Caron, M
    ELECTROPHORESIS, 2000, 21 (12) : 2566 - 2575
  • [28] A Hybrid Spectral Library and Protein Sequence Database Search Strategy for Bottom-Up and Top-Down Proteomic Data Analysis
    Dai, Yuling
    Millikin, Robert J.
    Rolfs, Zach
    Shortreed, Michael R.
    Smith, Lloyd M.
    JOURNAL OF PROTEOME RESEARCH, 2022, : 2609 - 2618
  • [29] Calibr improves spectral library search for spectrum-centric analysis of data independent acquisition proteomics
    Jen-Hung Wang
    Wai-Kok Choong
    Ching-Tai Chen
    Ting-Yi Sung
    Scientific Reports, 12
  • [30] Calibr improves spectral library search for spectrum-centric analysis of data independent acquisition proteomics
    Wang, Jen-Hung
    Choong, Wai-Kok
    Chen, Ching-Tai
    Sung, Ting-Yi
    SCIENTIFIC REPORTS, 2022, 12 (01)