Significance Analysis of INTeractome (SAINT) consists of a series of software tools for assigning confidence scores to protein-protein interactions based on quantitative proteomics data in AP-MS experiments. Semi-supervised SAINT models with controls are used for all experiments in this interaction repository. The version of the SAINT algorithm employed (SAINT with options or SAINTexpress) alongside modeling parameters is specified for each dataset. To learn more about SAINT with options, refer to the original publication "SAINT: probabilistic scoring of affinity purification - mass spectrometry data" (Nature Methods, 2011), or to the extended protocol paper "Analyzing protein-protein interactions from affinity purification-mass spectrometry data with SAINT" (Curr Protoc Bioinfo, 2012). SAINTexpress was published in J Proteomics in 2014 ("SAINTexpress: improvements and additional features in Significance Analysis of INTeractome software"). SAINT is the fruit of a collaboration between the Gingras, Choi and Nesvizhskii labs.


ProHits-viz generates a variety of high-quality, customizable images from protein-protein interaction data. Explicit support is provided for output from SAINT and the CRAPome, and generic support is provided for output from other tools. The interactive viewers within ProHits-viz can be used to visualize output from our tools directly in the browser. ProHits-web generates input files for ProHits-viz: simply select two of more baits from the "Explore baits" tabs of each project, and to download a tabular file in "SAINT" format, ready for visualization at ProHits-viz. For more information on ProHits-viz, see "Prohits-viz: a suite of web tools for visualizing interaction proteomics data" (Nature Methods, 2016). For details on the interface between ProHits-web and ProHits-viz, please refer to the user guide for Prohits-web (User guide).


The Laboratory Information Management Systems ProHits (ProHits-LIMS) is an open source software package designed to help scientists store, search and analyze mass spectrometry data, in particular for protein-protein interaction experiments. The complete platform provides secure storage of mass spectrometry data, integration with search engines and mass spectrometry analytical tools. For more information on ProHits features, see: "ProHits: integrated software for mass spectrometry-based interaction proteomics" (Nature Biotech, 2010). A simpler virtual machine version of ProHits is also available for downloads. For a detailed protocol in the download and use of ProHits, refer to: "Using ProHits to store, annotate and analyze affinity purification - mass spectrometry (AP-MS) data" (Curr Protoc Bioinfo, 2012). ProHits-LIMS V 4.0 enables analysis of Data Independent Acquisition data (see: "Data Independent Acquisition analysis in ProHits 4.0" , J Proteomics, 2016). All data in this repository are tracked at the Lunenfeld implementation of the ProHits system (or parallel implementations in other groups), and appropriate project, bait, experiment and sample numbers are provided as needed. ProHits was the results of a team effort by the Gingras and Tyers labs.

The CRAPome

The Contaminant Repository for Affinity Purification (CRAPome) is a database of negative control data for interaction proteomics experiments. It can be used to explore the contaminant propensity of individual proteins across multiple mass spectrometry experiments and generate frequent flier lists based on specific experimental parameters. Integration with SAINT and with simpler scoring tools enables users to employ controls in the CRAPome to help analyze their own data. See the publication "The CRAPome: a Contaminant Repository for Affinity Purification mass spectrometry data" (Nature Methods, 2013). An expanded resource, RePRINT (Resource for Evaluation of Protein INTeraction networks) is available for beta-testing at The CRAPome and RePRINT projects are co-led by A. Nesvizhskii and A.-C. Gingras, with the participation of laboratories worldwide.

Yeast Kinase and Phosphatase Interactome (KPI) Resource

This resource contains 1,844 high confidence interactions identified for yeast kinases and phosphatases as part of the manuscript "A global protein kinase and phosphatase network" (Science, 2010). This resource is the result of a collaboration between the Gingras, Nesvizhskii and Tyers groups.