Analyzing Protein‐Protein Interactions from Affinity Purification‐Mass Spectrometry Data with SAINT

Hyungwon Choi1, Guomin Liu2, Dattatreya Mellacheruvu3, Mike Tyers4, Anne‐Claude Gingras5, Alexey I. Nesvizhskii6

1 Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 2 Center for Systems Biology, Samuel Lunenfeld Research Institute at Mount Sinai Hospital, Toronto, Ontario, Canada, 3 Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, 4 Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, Québec, Canada and Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom, 5 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada, 6 Department of Pathology, University of Michigan, Ann Arbor, Michigan
Publication Name:  Current Protocols in Bioinformatics
Unit Number:  Unit 8.15
DOI:  10.1002/0471250953.bi0815s39
Online Posting Date:  September, 2012
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Significance Analysis of INTeractome (SAINT) is a software package for scoring protein‐protein interactions based on label‐free quantitative proteomics data (e.g., spectral count or intensity) in affinity purification–mass spectrometry (AP‐MS) experiments. SAINT allows bench scientists to select bona fide interactions and remove nonspecific interactions in an unbiased manner. However, there is no ‘one‐size‐fits‐all’ statistical model for every dataset, since the experimental design varies across studies. Key variables include the number of baits, the number of biological replicates per bait, and control purifications. Here we give a detailed account of input data format, control data, selection of high‐confidence interactions, and visualization of filtered data. We explain additional options for customizing the statistical model for optimal filtering in specific datasets. We also discuss a graphical user interface of SAINT in connection to the LIMS system ProHits, which can be installed as a virtual machine on Mac OS X or Windows computers. Curr. Protoc. Bioinform. 39:8.15.1‐8.15.23. © 2012 by John Wiley & Sons, Inc.

Keywords: protein‐protein interactions; label‐free quantitative proteomics; affinity purification–mass spectrometry (AP‐MS); statistical model

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Table of Contents

  • Introduction
  • Basic Protocol 1: Installation and Data Formatting
  • Basic Protocol 2: Running SAINT
  • Support Protocol 1: Visualization of Network
  • Alternate Protocol 1: Running SAINT Through ProHits Interface: Virtual Machine GUI
  • Guidelines for Understanding Results
  • Commentary
  • Literature Cited
  • Figures
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Basic Protocol 1: Installation and Data Formatting

  Necessary Resources
  • Installed SAINT software and reformatted input data
  • R package (http://cran.r‐
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