Luciphor is a program that performs phospho-site localization on MS/MS data processed by the Trans-Proteomic Pipeline (TPP). It is unique in that it is the first phospho-site prediction program to provide estimates for the false localization rate (FLR).
Key Publications:
In revew
Download: http://dfermin.github.com/luciphor

QPROT is a software for differential protein expression using MS1 and MS/MS-level continuous quantitative data. Features a hierarchical model with predictive recursive algorithm. Includes percentile normalization and multiple threading for fast computing.
Key Publications:
In review
Download: http://sourceforge.net/projects/qprot

Abacus is a tool for extracting adjusted spectral counts from the result XML files generated by the Trans-Proteomic Pipeline (TPP). Abacus outputs a tab-delimited file that can be used for label-free quantification or simply viewing proteomics results across multiple experimental runs. This program is written in JAVA and is platform independent.
Key Publications:
Abacus: A computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis. Fermin et al., Proteomics (2011) DOI:10.1002/pmic.201000650 Manuscript
Download: http://abacustpp.sf.net

A method for assigning confidence scores to protein-protein interactions in label-free quantitative AP-MS datasets. For each observed interaction with associated spectral count(s), SAINT constructs spectral count distributions for true and false hits from related interactions and derives the probability of true interaction. The modeling incorporates various data normalization steps and is also capable of utilizing the spectral counts from negative control purifications for improving specificity in small-to-intermediate scale experiments (available in SAINT v. 2.0). The method was initially develoed for label-free spectral count data, but was recently extended to MS1 intensity-based quantitative data as well (SAINT-MS1).
Key Publications:
SAINT v 1.0 (optimized for large scale datasets with no negative controls): Breitkreutz et al. Global architecture of the yeast kinome interaction network, Science 328, 1043 - 104 (2010)
SAINT v 2.0 Choi et al., Nature Methods (2010) DOI:doi:10.1038/nmeth.1541 Manuscript
SAINT-MS1 Choi et al., Journal of Proteome Research (2012) 11(4):2619-24 Manuscript
Download: http://saint-apms.sourceforge.net/

Software for the analysis of differential protein expression using label-free spectral count data. The hierarchical model of QSPEC pools statistical information for mean and variance estimates across all proteins in the presence of limited number of replicate data. In a typical quantitative proteomics experiment, there are rarely a sufficient number of replicates to render conventional statistic-based tests such as T-test applicable. QSPEC addresses this problem and calculates the ratio of likelihoods (Bayes Factor) for differential expression for each protein based on certain model assumptions (Poisson-family distributions for count data and Gaussian distribution for intensity data).
Key Publications:
Significance analysis of spectral count data in label-free shotgun proteomics. Choi H, Fermin D, Nesvizhskii AI. Mol Cell Proteomics. 2008 Dec;7(12):2373-85.
Web server: http://www.nesvilab.org/qspec.php/
Software download: http://qspec.sourceforge.net/

A biclustering method for constructing protein complexes using (filtered) high-confidence interaction data from label-free quantitative AP-MS experiment. The method forms bait clusters based on the similarity of quantitative interaction profiles as anchors of protein complexes, and identifies submatrices of prey proteins showing consistent quantitative association within the anchor bait clusters. The statistical model here determines the optimal number of bait clusters and prey clusters in the data, automatically yielding the configuration of highly probable protein complexes.
Key Publications:
Analysis of Protein Complexes via Model-based Biclustering of Label-free Quantitative AP-MS Data, H. Choi, S. Kim, A.C. Gingras, A.I. Nesvizhskii, Mol. Syst. Biol. 6:385 (2010)
Download: http://nestedcluster.sourceforge.net/

ProHits is a Laboratory Management System (LIMS) for interaction proteomics. The software was developed primarily by Anne-Claude Gingras and Mike Tyers labs. It integrates SAINT suite of tools for interaction scoring.
Key Publications:
ProHits: integrated software for mass spectrometry-based interaction proteomics, F. Liu et al., Nat Biotech, 2010.
Download: http://prohitsms.com/Prohits_download/list.php/

Core components of the open source data analysis pipeline (Trans-Proteomic Pipeline, TPP) for primary processing of mass spectrometry-based proteomic data. PeptideProphet performs statistical validation of peptide identifications from tandem mass (MS/MS) spectra. It can analyze the results of all most commonly used MS/MS database search tools, including SEQUEST, MASCOT, and X! Tandem. iProphet further improves upon PeptideProphet modeling and allows integration of multiple search tools. ProteinProphet continues the analysis at the protein level. It accurately addresses the protein inference problem of shared peptides (peptides present in multiple protein database entries), estimates the number of correct protein identifications in a dataset, as well as the false discovery rates (FDR). TPP also includes tools for viewing raw LC/MS data, peptide quantification, spectral quality scoring, and other useful tools. The pipeline is maintained by the Seattle Proteomics Center at the Institute for Systems Biology http://www.systemsbiology.org/.
Key Publications:
PeptideProphet: Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Keller A, Nesvizhskii AI, Kolker E, Aebersold R. Anal Chem. 2002 Oct 15;74(20):5383-92.
ProteinProphet: A statistical model for identifying proteins by tandem mass spectrometry. Nesvizhskii AI, Keller A, Kolker E, Aebersold R. Anal Chem. 2003 Sep 1;75(17):4646-58.
iProphet: In preparation.
Review: Analysis and validation of proteomic data generated by tandem mass spectrometry. Nesvizhskii AI, Vitek O, Aebersold R. Nat Methods. 2007 Oct;4(10):787-97.
Download: http://tools.proteomecenter.org/wiki/index.php?title=Software:TPP
Google Discussion Group: http://groups.google.com/group/spctools-discuss