PeptideProphet

PeptideProphet is a computational tool used in the field of proteomics to assign confidence levels to peptide identifications made by tandem mass spectrometry. It is a component of the Trans-Proteomic Pipeline (TPP), a suite of open-source bioinformatics tools developed by the Seattle Proteome Center.

Overview

PeptideProphet uses statistical modeling to evaluate the probability that a given peptide identification is correct. It takes into account various factors, such as the quality of the mass spectrum, the match between the observed and theoretical fragmentation pattern, and the presence of certain post-translational modifications. The output is a probability score for each peptide identification, which can be used to filter the data and control the false discovery rate.

Algorithm

The PeptideProphet algorithm works by fitting a mixture model to the distribution of scores assigned to peptide identifications by a search engine such as SEQUEST or Mascot. The model assumes that the distribution is a mixture of two components: one corresponding to correct identifications, and the other to incorrect ones. The parameters of the model are estimated using the Expectation-Maximization algorithm, and the probability that a given identification is correct is computed based on these parameters.

Usage

PeptideProphet is typically used in conjunction with other tools in the TPP, such as SpectraST for spectral library searching, and ProteinProphet for protein inference. The results can be visualized and analyzed using the TPP's graphical user interface, PeptideProphetViewer.

See also

• Proteomics
• Mass spectrometry
• Bioinformatics
• Trans-Proteomic Pipeline