Trans-Proteomic Pipeline

Last updated
TPP
Developer(s) Institute for Systems Biology
Initial release10 December 2004;20 years ago (2004-12-10)
Stable release
5.0.0 / 11 October 2016;8 years ago (2016-10-11) [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.

Contents

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. [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 a false discovery rate (FDR) on protein level. [7]

Spectral library handling

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

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
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.