Scoring Large‐Scale Affinity Purification Mass Spectrometry Datasets with MiST

Erik Verschueren1, John Von Dollen1, Peter Cimermancic1, Natali Gulbahce2, Andrej Sali1, Nevan J. Krogan1

1 California Institute for Quantitative Biomedical Sciences, San Francisco, California, 2 Department of Cellular & Molecular Pharmacology, University of California, San Francisco, San Francisco, California
Publication Name:  Current Protocols in Bioinformatics
Unit Number:  Unit 8.19
DOI:  10.1002/0471250953.bi0819s49
Online Posting Date:  March, 2015
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Abstract

High‐throughput Affinity Purification Mass Spectrometry (AP‐MS) experiments can identify a large number of protein interactions, but only a fraction of these interactions are biologically relevant. Here, we describe a comprehensive computational strategy to process raw AP‐MS data, perform quality controls, and prioritize biologically relevant bait‐prey pairs in a set of replicated AP‐MS experiments with Mass spectrometry interaction STatistics (MiST). The MiST score is a linear combination of prey quantity (abundance), abundance invariability across repeated experiments (reproducibility), and prey uniqueness relative to other baits (specificity). We describe how to run the full MiST analysis pipeline in an R environment and discuss a number of configurable options that allow the lay user to convert any large‐scale AP‐MS data into an interpretable, biologically relevant protein‐protein interaction network. © 2015 by John Wiley & Sons, Inc.

Keywords: affinity purification mass spectrometry; protein interactions; scoring algorithms; interaction networks; proteomics

     
 
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Table of Contents

  • Introduction
  • Basic Protocol 1: Data Pre‐Processing
  • Basic Protocol 2: Quality Control
  • Basic Protocol 3: Calculating the MiST Score
  • Support Protocol 1: Installation of MiST
  • Guidelines for Understanding Results
  • Commentary
  • Figures
  • Tables
     
 
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Materials

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Literature Cited

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Internet Resources
  https://github.com/everschueren/MiST/
  The Github repository is the main online resource for this unit. We have opened the MiST repository to the public but currently it is only editable by approved collaborators. In the near future we will also update the webpage at http://modbase.compbio.ucsf.edu/MiST/ to reflect the protocols described in this manuscript.
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