Literature DB >> 18216375

Comparison of Mascot and X!Tandem performance for low and high accuracy mass spectrometry and the development of an adjusted Mascot threshold.

Markus Brosch1, Sajani Swamy, Tim Hubbard, Jyoti Choudhary.   

Abstract

It is a major challenge to develop effective sequence database search algorithms to translate molecular weight and fragment mass information obtained from tandem mass spectrometry into high quality peptide and protein assignments. We investigated the peptide identification performance of Mascot and X!Tandem for mass tolerance settings common for low and high accuracy mass spectrometry. We demonstrated that sensitivity and specificity of peptide identification can vary substantially for different mass tolerance settings, but this effect was more significant for Mascot. We present an adjusted Mascot threshold, which allows the user to freely select the best trade-off between sensitivity and specificity. The adjusted Mascot threshold was compared with the default Mascot and X!Tandem scoring thresholds and shown to be more sensitive at the same false discovery rates for both low and high accuracy mass spectrometry data.

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Year:  2008        PMID: 18216375      PMCID: PMC2656932          DOI: 10.1074/mcp.M700293-MCP200

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  28 in total

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4.  Characterization of peptides bound to the class I MHC molecule HLA-A2.1 by mass spectrometry.

Authors:  D F Hunt; R A Henderson; J Shabanowitz; K Sakaguchi; H Michel; N Sevilir; A L Cox; E Appella; V H Engelhard
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5.  The Orbitrap: a new mass spectrometer.

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7.  A probability-based approach for high-throughput protein phosphorylation analysis and site localization.

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Authors:  Junmin Peng; Joshua E Elias; Carson C Thoreen; Larry J Licklider; Steven P Gygi
Journal:  J Proteome Res       Date:  2003 Jan-Feb       Impact factor: 4.466

9.  Direct analysis and identification of proteins in mixtures by LC/MS/MS and database searching at the low-femtomole level.

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10.  Status of complete proteome analysis by mass spectrometry: SILAC labeled yeast as a model system.

Authors:  Lyris M F de Godoy; Jesper V Olsen; Gustavo A de Souza; Guoqing Li; Peter Mortensen; Matthias Mann
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  23 in total

Review 1.  Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology.

Authors:  Wenjiang J Fu; Arnold J Stromberg; Kert Viele; Raymond J Carroll; Guoyao Wu
Journal:  J Nutr Biochem       Date:  2010-03-16       Impact factor: 6.048

2.  Data analysis strategy for maximizing high-confidence protein identifications in complex proteomes such as human tumor secretomes and human serum.

Authors:  Huan Wang; Hsin-Yao Tang; Glenn C Tan; David W Speicher
Journal:  J Proteome Res       Date:  2011-10-18       Impact factor: 4.466

3.  Snapshot peptidomics of the regulated secretory pathway.

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4.  Bayesian nonparametric model for the validation of peptide identification in shotgun proteomics.

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Review 5.  A face in the crowd: recognizing peptides through database search.

Authors:  Jimmy K Eng; Brian C Searle; Karl R Clauser; David L Tabb
Journal:  Mol Cell Proteomics       Date:  2011-08-29       Impact factor: 5.911

Review 6.  Protein analysis by shotgun/bottom-up proteomics.

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7.  Sialic acid-focused quantitative mouse serum glycoproteomics by multiple reaction monitoring assay.

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Journal:  Mol Cell Proteomics       Date:  2010-06-22       Impact factor: 5.911

8.  Evaluation of the Consensus of Four Peptide Identification Algorithms for Tandem Mass Spectrometry Based Proteomics.

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9.  Adaptive discriminant function analysis and reranking of MS/MS database search results for improved peptide identification in shotgun proteomics.

Authors:  Ying Ding; Hyungwon Choi; Alexey I Nesvizhskii
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10.  Database search strategies for proteomic data sets generated by electron capture dissociation mass spectrometry.

Authors:  Steve M M Sweet; Andrew W Jones; Debbie L Cunningham; John K Heath; Andrew J Creese; Helen J Cooper
Journal:  J Proteome Res       Date:  2009-12       Impact factor: 4.466

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