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ProHits-viz: a suite of web tools for visualizing interaction proteomics data

Nature Methods volume 14, pages 645–646 (2017)Cite this article

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To the Editor: With the broad availability of mass spectrometry methods for identifying protein–protein interactions, there is a growing need for applications that can simplify the challenges associated with managing, analyzing and visualizing the results obtained by these methods. Here we present ProHits-viz (prohits-viz.lunenfeld.ca), a suite of web-based tools for visualizing and analyzing protein interaction data.

ProHits-viz consists of four data analysis and image generation tools complemented by interactive viewers. The analysis tools can (i) cluster baits and preys for dot plot images, (ii) perform correlation analysis, (iii) calculate prey specificity scores and (iv) generate detailed bait–bait comparisons. Dot plots are a simple way of summarizing protein interaction data5, displaying raw prey abundance, relative prey abundance across baits and prey confidence (Fig. 1b,c). The correlation analysis tool performs both bait and prey correlation and visualizes the results as clustered heat maps (Fig. 1d). Correlation of prey–prey profiles is particularly valuable for large data sets and offers an alternative prey-centric means of visualizing data that aids in identifying preys that may colocalize, belong to the same complex or even be direct interactors. The specificity tool is useful for medium-to-large data sets and calculates prey specificity scores for each prey–bait pair (Fig. 1e). The specificity scores are helpful in identifying preys preferentially associated with one or a small number of baits amongst a number of related baits. Available scores include a crude fold-enrichment calculation as well as reimplementation of scores from the Comparative Proteomics Analysis Software Suite (CompPASS)2. Finally, the bait–bait comparison tool takes information on two baits, as selected by the user, and plots their significant preys in a way that allows for comparison in a compact scatterplot (Supplementary Protocol). Results from each analytical tool at ProHits-viz can be passed directly to interactive visualization interfaces or downloaded as a folder that contains images in PDF format. Details about each tool and usage options can be found in the Supplementary Protocol and Supplementary Methods.

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Figure 1: ProHits-viz at a glance.

References

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Acknowledgements

We are grateful to all members of the Gingras lab for feedback on ProHits-viz, particularly J.-Y. Youn and A.L. Couzens for comments during manuscript preparation. We would also like to thank D. Mellacheruvu for providing ProHits-viz-compatible downloadable files on the CRAPome website. We acknowledge funding from the Government of Canada through Genome Canada and the Ontario Genomics Institute (grant nos. OGI-088 and OGI-097 to A.-C.G. and L.P.), the Canadian Institutes of Health Research (to A.-C.G.; Foundation grant no. FDN143301); the US National Institutes of Health (to A.I.N. and A.-C.G.; grant no. 5R01GM94231); and the Singapore Ministry of Education (to H.C.; grant no. MOE T2-2-084). A.-C.G. is the Canada Research Chair in Functional Proteomics and the Lea Reichmann Chair in Cancer Proteomics.

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Authors and Affiliations

  1. Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada

    James D R Knight, Gagan D Gupta, Laurence Pelletier & Anne-Claude Gingras

  2. Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore

    Hyungwon Choi

  3. Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research, Singapore

    Hyungwon Choi

  4. Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada

    Laurence Pelletier & Anne-Claude Gingras

  5. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada

    Brian Raught

  6. Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada

    Brian Raught

  7. Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA

    Alexey I Nesvizhskii

  8. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA

    Alexey I Nesvizhskii

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  1. James D R Knight
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  6. Alexey I Nesvizhskii
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  7. Anne-Claude Gingras
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Correspondence to Anne-Claude Gingras.

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Integrated supplementary information

Supplementary Figure 1 Snapshot of the available parameters for the dot plot analytical tool.

Default options are shown; alternative options can be selected through dropdown menus or values can be typed in. SAINT and CRAPome analytical pipeline outputs are explicitly supported (columns are pre-recognized). When inputting another format, the user will be prompted to specify the score directionality. Parameters and clustering options are defined in the text and in the user manuals (available in the Supplementary Protocol).

Supplementary information

Supplementary Text and Figures

Supplementary Figure 1 and Supplementary Methods

Supplementary Protocol

ProHits-viz

Supplementary Table 1

Sample data set for use with ProHits-viz.

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Knight, J., Choi, H., Gupta, G. et al. ProHits-viz: a suite of web tools for visualizing interaction proteomics data. Nat Methods 14, 645–646 (2017). https://doi.org/10.1038/nmeth.4330

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