Trans-Proteomic Pipeline

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TPP
Developer(s) Institute for Systems Biology
Initial release 10 December 2004; 9 years ago (2004-12-10)
Stable release 4.6.2 / 15 February 2013; 20 months ago (2013-02-15)[1]
Written in C++, Perl, Java
Operating system Linux, Windows, OS X
Type Bioinformatics / Mass spectrometry software
License GPL v. 2.0 and LGPL
Website TPP Wiki

The Trans-Proteomic Pipeline (TPP) is an open-source data analysis software for proteomics developed at the Institute for Systems Biology (ISB) by the Ruedi Aebersold group under the Seattle Proteome Center. The TPP includes PeptideProphet,[2] ProteinProphet, [3] ASAPRatio, XPRESS and Libra.

Software Components[edit]

Probability Assignment and Validation[edit]

PeptideProphet performs statistical validation of peptide-spectra-matches (PSM) using the results of search engines by estimating an false discovery rate (FDR) on PSM level.[4] The initial PeptideProphet used a fit of a Gaussian distribution for the correct identifications and a fit of a gamma distribution for the incorrect identification. A later modification of the program allowed the usage of a target-decoy approach, using either a variable component mixture model or a semi-parametric mixture model.[5] In the PeptideProphet, specifying a decoy tag will use the variable component mixture model while selecting a non-parametric model will use the semi-parametric mixture model.

ProteinProphet identifies proteins based on the results of PeptideProphet.[6]

Mayu performs statistical validation of protein identification by estimating an False Discovery Rate (FDR) on protein level.[7]

Spectral library handling[edit]

The SpectraST tool is able to generate spectral libraries and search datasets using these libraries.[8]

See also[edit]

References[edit]

  1. ^ TPP 4.6.2 Release is Available
  2. ^ Software:PeptideProphet - SPCTools
  3. ^ Software:ProteinProphet - SPCTools
  4. ^ Keller A, Nesvizhskii A, Kolker E, and Aebersold R. (2002) "Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search." Anal Chem 74:5383–5392.
  5. ^ Choi, Hyungwon; Ghosh, Debashis; Nesvizhskii, Alexey I. (2008). "Statistical Validation of Peptide Identifications in Large-Scale Proteomics Using the Target-Decoy Database Search Strategy and Flexible Mixture Modeling". Journal of Proteome Research 7 (1): 286–292. doi:10.1021/pr7006818. ISSN 1535-3893. 
  6. ^ Nesvizhskii AI, Keller A, Kolker E, Aebersold R. (2003) "A statistical model for identifying proteins by tandem mass spectrometry." Anal Chem 75:4646-58
  7. ^ Reiter, L.; Claassen, M.; Schrimpf, SP.; Jovanovic, M.; Schmidt, A.; Buhmann, JM.; Hengartner, MO.; Aebersold, R. (Nov 2009). "Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry.". Mol Cell Proteomics 8 (11): 2405–17. doi:10.1074/mcp.M900317-MCP200. PMID 19608599. 
  8. ^ Software:SpectraST - SPCTools