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Trans-Proteomic Pipeline

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TPP
Developer(s)Institute for Systems Biology
Initial release10 December 2004; 19 years ago (2004-12-10)
Stable release5.0.0 / 11 October 2016; 8 years ago (2016-10-11)
Written inC++, Perl, Java
Operating systemLinux, Windows, OS X
TypeBioinformatics / Mass spectrometry software
LicenseGPL v. 2.0 and LGPL
WebsiteTPP 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, ProteinProphet, ASAPRatio, XPRESS and Libra.

Software Components

Probability Assignment and Validation

PeptideProphet performs statistical validation of peptide-spectra-matches (PSM) using the results of search engines by estimating a false discovery rate (FDR) on PSM level. 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. 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.

Mayu performs statistical validation of protein identification by estimating a false discovery rate (FDR) on protein level.

Spectral library handling

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

See also

References

  1. TPP 5.0.0 Release is Available
  2. Software:PeptideProphet - SPCTools
  3. Software:ProteinProphet - SPCTools
  4. Keller, A; Nesvizhskii, A; Kolker, E; Aebersold, R. (2002). "Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search". Anal Chem. 74 (20): 5383–5392. doi:10.1021/ac025747h. PMID 12403597.
  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" (PDF). Journal of Proteome Research. 7 (1): 286–292. doi:10.1021/pr7006818. ISSN 1535-3893. PMID 18078310.
  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. PMC 2773710. PMID 19608599.
  8. Software:SpectraST - SPCTools
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