Software:PeptideProphet
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Current revision Jesse j (Talk | contribs) (→In a nutshell) |
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| + | ==Getting the software== | ||
| '''This software is included in the current [[Software:TPP|TPP]] distribution.''' | '''This software is included in the current [[Software:TPP|TPP]] distribution.''' | ||
| - | PeptideProphet is a tool for generating statistical validation of MS/MS search engines' spectra-to-peptide sequence assignments. This tool was orginally develped at the SPC, part of the ISB. PeptideProphet is now an core part of the Trans-Proteomic Pipeline software distrubtion. | + | ==In a nutshell== |
| + | PeptideProphet is a tool for generating statistical validation of MS/MS search engines' spectra-to-peptide sequence assignments. This tool was orginally develped at the SPC, part of the ISB. PeptideProphet is now a core part of the Trans-Proteomic Pipeline software distrubtion. | ||
| - | Reference: Keller A, Nesvizhskii AI, Kolker E, Aebersold R. (2002) "Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search." Anal Chem 74:5383-92. [http://tools.proteomecenter.org/publications/Keller.AnalChem.02.pdf download PDF] | + | ==More info== |
| + | A robust and accurate statistical approach, based on the expectation maximization algorithm, for validation of peptide identifications made by tandem mass spectrometry (MS/MS) and database searching. By employing database search scores, number of tryptic termini, number of missed cleavages, and other information, the method learns to distinguish correctly from incorrectly assigned peptides in the data set and computes for each peptide assignment to an MS/MS spectrum a probability of being correct. We show that using the probabilities computed from the model, one can achieve much higher sensitivity for any given error rate compared to the results of using conventional filtering criteria. The method enables high-throughput analysis of proteomics data by eliminating the need to manually validate database search results. In addition, it can facilitate the benchmarking of various experimental procedures and serve as a common standard by which the results of different experimental groups can be compared. | ||
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| + | ==Reference== | ||
| + | Keller A, Nesvizhskii AI, Kolker E, Aebersold R. (2002) "Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search." Anal Chem 74:5383-92. [http://tools.proteomecenter.org/publications/Keller.AnalChem.02.pdf download PDF] | ||
Current revision
Contents |
Getting the software
This software is included in the current TPP distribution.
In a nutshell
PeptideProphet is a tool for generating statistical validation of MS/MS search engines' spectra-to-peptide sequence assignments. This tool was orginally develped at the SPC, part of the ISB. PeptideProphet is now a core part of the Trans-Proteomic Pipeline software distrubtion.
More info
A robust and accurate statistical approach, based on the expectation maximization algorithm, for validation of peptide identifications made by tandem mass spectrometry (MS/MS) and database searching. By employing database search scores, number of tryptic termini, number of missed cleavages, and other information, the method learns to distinguish correctly from incorrectly assigned peptides in the data set and computes for each peptide assignment to an MS/MS spectrum a probability of being correct. We show that using the probabilities computed from the model, one can achieve much higher sensitivity for any given error rate compared to the results of using conventional filtering criteria. The method enables high-throughput analysis of proteomics data by eliminating the need to manually validate database search results. In addition, it can facilitate the benchmarking of various experimental procedures and serve as a common standard by which the results of different experimental groups can be compared.
Reference
Keller A, Nesvizhskii AI, Kolker E, Aebersold R. (2002) "Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search." Anal Chem 74:5383-92. download PDF
