Unit

UNIT 8.19 Scoring Large-Scale Affinity Purification Mass Spectrometry Datasets with MiST

  1. Erik Verschueren1,6,
  2. John Von Dollen1,6,
  3. Peter Cimermancic1,3,6,
  4. Natali Gulbahce1,
  5. Andrej Sali4,5,6,
  6. Nevan J. Krogan1,2,6

Published Online: 9 MAR 2015

DOI: 10.1002/0471250953.bi0819s49

Current Protocols in Bioinformatics

Current Protocols in Bioinformatics

How to Cite

Verschueren, E., Von Dollen, J., Cimermancic, P., Gulbahce, N., Sali, A., and Krogan, N. 2015. Scoring Large-Scale Affinity Purification Mass Spectrometry Datasets with MiST. Curr. Protoc. Bioinform. 49:8.19.1-8.19.16. doi: 10.1002/0471250953.bi0819s49

Author Information

  1. 1

    Department of Cellular & Molecular Pharmacology, University of California, San Francisco, San Francisco, California

  2. 2

    Gladstone Institutes, University of California, San Francisco, San Francisco, California

  3. 3

    Graduate Group in Biological and Medical Informatics, University of California, San Francisco, San Francisco, California

  4. 4

    Department of Bioengineering and Therapeutic Science, University of California, San Francisco, San Francisco, California

  5. 5

    Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California

  6. 6

    California Institute for Quantitative Biomedical Sciences, San Francisco, California

Publication History

  1. Published Online: 9 MAR 2015

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