Literature DB >> 23808827

Spectral library generating function for assessing spectrum-spectrum match significance.

Mingxun Wang1, Nuno Bandeira.   

Abstract

Tandem mass spectrometry (MS/MS) continues to be the technology of choice for high-throughput analysis of complex proteomics samples. While MS/MS spectra are commonly identified by matching against a database of known protein sequences, the complementary approach of spectral library searching against collections of reference spectra consistently outperforms sequence-based searches by resulting in significantly more identified spectra. However, while spectral library searches benefit from the advance knowledge of the expected peptide fragmentation patterns recorded in library spectra, estimation of the statistical significance of spectrum-spectrum matches (SSMs) continues to be hindered by difficulties in finding an appropriate definition of "random" SSMs to use as a null model when estimating the significance of true SSMs. We propose to avoid this problem by changing the null hypothesis: instead of determining the probability of observing a high SSM score between randomly matched spectra, we estimate the probability of observing a low SSM score between replicate spectra of the same molecule. To this end, we explicitly model the variation in instrument measurements of MS/MS peak intensities and show how these models can be used to determine a theoretical distribution of SSM scores between reference and query spectra of the same molecule. While the proposed spectral library generating function (SLGF) approach can be used to calculate theoretical distributions for any additive SSM score (e.g., any dot product), we further show how it can be used to calculate the distribution of expected cosines between reference and query spectra. We developed a spectral library search tool, Tremolo, and demonstrate that this SLGF-based search tool significantly outperforms current state-of-the-art spectral library search tools and provide a detailed discussion of the multiple reasons behind the observed differences in the sets of identified MS/MS spectra.

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Year:  2013        PMID: 23808827      PMCID: PMC3766387          DOI: 10.1021/pr400230p

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  22 in total

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Authors:  Sangtae Kim; Nikolai Mischerikow; Nuno Bandeira; J Daniel Navarro; Louis Wich; Shabaz Mohammed; Albert J R Heck; Pavel A Pevzner
Journal:  Mol Cell Proteomics       Date:  2010-09-09       Impact factor: 5.911

3.  Peptide identification from mixture tandem mass spectra.

Authors:  Jian Wang; Josué Pérez-Santiago; Jonathan E Katz; Parag Mallick; Nuno Bandeira
Journal:  Mol Cell Proteomics       Date:  2010-03-27       Impact factor: 5.911

4.  Using annotated peptide mass spectrum libraries for protein identification.

Authors:  R Craig; J C Cortens; D Fenyo; R C Beavis
Journal:  J Proteome Res       Date:  2006-08       Impact factor: 4.466

5.  Development and validation of a spectral library searching method for peptide identification from MS/MS.

Authors:  Henry Lam; Eric W Deutsch; James S Eddes; Jimmy K Eng; Nichole King; Stephen E Stein; Ruedi Aebersold
Journal:  Proteomics       Date:  2007-03       Impact factor: 3.984

6.  Artificial decoy spectral libraries for false discovery rate estimation in spectral library searching in proteomics.

Authors:  Henry Lam; Eric W Deutsch; Ruedi Aebersold
Journal:  J Proteome Res       Date:  2010-01       Impact factor: 4.466

7.  Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry.

Authors:  David L Tabb; Lorenzo Vega-Montoto; Paul A Rudnick; Asokan Mulayath Variyath; Amy-Joan L Ham; David M Bunk; Lisa E Kilpatrick; Dean D Billheimer; Ronald K Blackman; Helene L Cardasis; Steven A Carr; Karl R Clauser; Jacob D Jaffe; Kevin A Kowalski; Thomas A Neubert; Fred E Regnier; Birgit Schilling; Tony J Tegeler; Mu Wang; Pei Wang; Jeffrey R Whiteaker; Lisa J Zimmerman; Susan J Fisher; Bradford W Gibson; Christopher R Kinsinger; Mehdi Mesri; Henry Rodriguez; Stephen E Stein; Paul Tempst; Amanda G Paulovich; Daniel C Liebler; Cliff Spiegelman
Journal:  J Proteome Res       Date:  2010-02-05       Impact factor: 4.466

8.  Spectral probabilities and generating functions of tandem mass spectra: a strike against decoy databases.

Authors:  Sangtae Kim; Nitin Gupta; Pavel A Pevzner
Journal:  J Proteome Res       Date:  2008-07-03       Impact factor: 4.466

9.  Directed sample interrogation utilizing an accurate mass exclusion-based data-dependent acquisition strategy (AMEx).

Authors:  Emily L Rudomin; Steven A Carr; Jacob D Jaffe
Journal:  J Proteome Res       Date:  2009-06       Impact factor: 4.466

10.  Spectrum-to-spectrum searching using a proteome-wide spectral library.

Authors:  Chia-Yu Yen; Stephane Houel; Natalie G Ahn; William M Old
Journal:  Mol Cell Proteomics       Date:  2011-04-30       Impact factor: 5.911

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  5 in total

1.  Spectral Library Search Improves Assignment of TMT Labeled MS/MS Spectra.

Authors:  Jianqiao Shen; Vishwajeeth R Pagala; Alex M Breuer; Junmin Peng; Xusheng Wang
Journal:  J Proteome Res       Date:  2018-08-16       Impact factor: 4.466

Review 2.  Expanding the Use of Spectral Libraries in Proteomics.

Authors:  Eric W Deutsch; Yasset Perez-Riverol; Robert J Chalkley; Mathias Wilhelm; Stephen Tate; Timo Sachsenberg; Mathias Walzer; Lukas Käll; Bernard Delanghe; Sebastian Böcker; Emma L Schymanski; Paul Wilmes; Viktoria Dorfer; Bernhard Kuster; Pieter-Jan Volders; Nico Jehmlich; Johannes P C Vissers; Dennis W Wolan; Ana Y Wang; Luis Mendoza; Jim Shofstahl; Andrew W Dowsey; Johannes Griss; Reza M Salek; Steffen Neumann; Pierre-Alain Binz; Henry Lam; Juan Antonio Vizcaíno; Nuno Bandeira; Hannes Röst
Journal:  J Proteome Res       Date:  2018-10-11       Impact factor: 4.466

3.  Significance estimation for large scale metabolomics annotations by spectral matching.

Authors:  Kerstin Scheubert; Franziska Hufsky; Daniel Petras; Mingxun Wang; Louis-Félix Nothias; Kai Dührkop; Nuno Bandeira; Pieter C Dorrestein; Sebastian Böcker
Journal:  Nat Commun       Date:  2017-11-14       Impact factor: 14.919

4.  Taxonomically Informed Scoring Enhances Confidence in Natural Products Annotation.

Authors:  Adriano Rutz; Miwa Dounoue-Kubo; Simon Ollivier; Jonathan Bisson; Mohsen Bagheri; Tongchai Saesong; Samad Nejad Ebrahimi; Kornkanok Ingkaninan; Jean-Luc Wolfender; Pierre-Marie Allard
Journal:  Front Plant Sci       Date:  2019-10-25       Impact factor: 5.753

5.  SIMILE enables alignment of tandem mass spectra with statistical significance.

Authors:  Daniel G C Treen; Mingxun Wang; Shipei Xing; Katherine B Louie; Tao Huan; Pieter C Dorrestein; Trent R Northen; Benjamin P Bowen
Journal:  Nat Commun       Date:  2022-05-06       Impact factor: 17.694

  5 in total

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