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Clustering and Network Analysis of Reverse Phase Protein Array Data

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Molecular Profiling

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1606))

Abstract

Molecular profiling of proteins and phosphoproteins using a reverse phase protein array (RPPA) platform, with a panel of target-specific antibodies, enables the parallel, quantitative proteomic analysis of many biological samples in a microarray format. Hence, RPPA analysis can generate a high volume of multidimensional data that must be effectively interrogated and interpreted. A range of computational techniques for data mining can be applied to detect and explore data structure and to form functional predictions from large datasets. Here, two approaches for the computational analysis of RPPA data are detailed: the identification of similar patterns of protein expression by hierarchical cluster analysis and the modeling of protein interactions and signaling relationships by network analysis. The protocols use freely available, cross-platform software, are easy to implement, and do not require any programming expertise. Serving as data-driven starting points for further in-depth analysis, validation, and biological experimentation, these and related bioinformatic approaches can accelerate the functional interpretation of RPPA data.

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Acknowledgments

A.B. is funded by Cancer Research UK (grant C157/A15703 to M. C. Frame).

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  1. Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XR, UK

    Adam Byron

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  1. Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia, USA

    Virginia Espina

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Byron, A. (2017). Clustering and Network Analysis of Reverse Phase Protein Array Data. In: Espina, V. (eds) Molecular Profiling. Methods in Molecular Biology, vol 1606. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6990-6_12

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  • DOI: https://doi.org/10.1007/978-1-4939-6990-6_12

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