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A general pipeline for quality and statistical assessment of protein interaction data using R and Bioconductor

Nature Protocols volume 4, pages 535–546 (2009)Cite this article

Abstract

The systematic mapping of protein interactions by bait–prey techniques, including affinity purification-mass spectrometry or the yeast two-hybrid system, contributes a unique and relevant perspective on the comprehensive picture of cellular machines. We describe here a protocol for statistical analysis of node-and-edge graph representations of these data using R and Bioconductor, recognizing that steps may be added or omitted depending on the data set at hand. The fundamental purpose of such analyses is feature estimation, defined here as the estimation of data-type-specific biological features, such as protein complex composition and the physical interaction integrity of known or estimated complexes. In preparation for feature estimation tasks, we outline a progression through three analytic components common to all bait–prey data types: preliminary setup, exploratory analysis and quality assessment. The end result is a collection of descriptive and inferred characteristics of the data, ready for biological interpretation in a computationally tractable form.

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Figure 1: Seven ordered pairs representing protein interaction (bait, prey) pairs.
Figure 2: Flowchart describing the outline of analyses presented in this protocol.
Figure 3: Viable protein levels encapsulated in bar charts for the AP-MS experiments.
Figure 4: A screenshot of the html page that provides a user-friendly interface for the output of the hypergeometric test for functional category overrepresentation.
Figure 5: Scatter plots corresponding to the in- and out-degree for each VBP of Gavin06.
Figure 6: Estimate of PTP and PFP for Gavin06 AP-MS data using the GS ScISIC reference data set and a manifold of possible solutions.
Figure 7: This graph renders all the proteins found to interact with the preselected bait protein LSM5 (YER146W) within the Gavin06 data set.
Figure 8: Two examples of complex estimates using the apComplex algorithm.
Figure 9: An apComplex estimate with overlaid Y2H data from Ito et al.3 and Uetz et al.1 experiments.

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Acknowledgements

We thank the reviewers for their insightful and useful critique of this manuscript. We also thank Wolfgang Huber, Robert Gentleman, Simon Anders and especially Sandra Orchard for their comments and suggestions as this manuscript evolved. T.C. has been supported by the Human Frontiers Science Program Grant (HFSP/LIP0442/2005) as well as the Ferris Fund from King's College, Cambridge University.

Author information

Authors and Affiliations

  1. EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK

    Tony Chiang

  2. Department of Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

    Tony Chiang

  3. Department of Preventive Medicine, Northwestern University, Chicago, Illinois, USA

    Denise Scholtens

Authors
  1. Tony Chiang
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Corresponding author

Correspondence to Denise Scholtens.

Supplementary information

41596_2009_BFnprot200926_MOESM427_ESM.pdf

Supplementary Fig. 1: directedGraph.pdf is a figure file cited in the vignette-style document ppiProtocol.Rnw. (PDF 181 kb)

Supplementary Fig. 2: flowChart.pdf is a figure file cited in the vignette-style document ppiProtocol.Rnw. (PDF 197 kb)

41596_2009_BFnprot200926_MOESM429_ESM.jpg

Supplementary Fig. 3: Gavin2006Screenshot.png is a figure file cited in the vignette-style document ppiProtocol.Rnw. (JPG 163 kb)

41596_2009_BFnprot200926_MOESM430_ESM.zip

Supplementary Method 1: ppiProtocol.Rnw is a vignette-style document file weaving together the text and code contained in this protocol so that users can reproduce the analysis results. (ZIP 18 kb)

41596_2009_BFnprot200926_MOESM431_ESM.zip

Supplementary Method 2: ppiProtocol.R contains the R code used in the analyses presented in this protocol without the accompanying text. (ZIP 3 kb)

41596_2009_BFnprot200926_MOESM432_ESM.zip

Supplementary Method 3: ppiProtocol.bib is a Bibtex file containing the references cited in this document and used in ppiProtocol.Rnw. (ZIP 4 kb)

41596_2009_BFnprot200926_MOESM433_ESM.zip

Supplementary Data 1: ppiProtocolData_1.1.0.tar.gz is an R data package containing all data sets used in this protocol. (ZIP 12073 kb)

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Chiang, T., Scholtens, D. A general pipeline for quality and statistical assessment of protein interaction data using R and Bioconductor. Nat Protoc 4, 535–546 (2009). https://doi.org/10.1038/nprot.2009.26

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