BMC Bioinformatics (Dec 2008)

RPPAML/RIMS: A metadata format and an information management system for reverse phase protein arrays

  • Hennessy Bryan T,
  • Coombes Kevin,
  • Deus Helena F,
  • Carey Mark,
  • Stanislaus Romesh,
  • Mills Gordon B,
  • Almeida Jonas S

DOI
https://doi.org/10.1186/1471-2105-9-555
Journal volume & issue
Vol. 9, no. 1
p. 555

Abstract

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Abstract Background Reverse Phase Protein Arrays (RPPA) are convenient assay platforms to investigate the presence of biomarkers in tissue lysates. As with other high-throughput technologies, substantial amounts of analytical data are generated. Over 1000 samples may be printed on a single nitrocellulose slide. Up to 100 different proteins may be assessed using immunoperoxidase or immunoflorescence techniques in order to determine relative amounts of protein expression in the samples of interest. Results In this report an RPPA Information Management System (RIMS) is described and made available with open source software. In order to implement the proposed system, we propose a metadata format known as reverse phase protein array markup language (RPPAML). RPPAML would enable researchers to describe, document and disseminate RPPA data. The complexity of the data structure needed to describe the results and the graphic tools necessary to visualize them require a software deployment distributed between a client and a server application. This was achieved without sacrificing interoperability between individual deployments through the use of an open source semantic database, S3DB. This data service backbone is available to multiple client side applications that can also access other server side deployments. The RIMS platform was designed to interoperate with other data analysis and data visualization tools such as Cytoscape. Conclusion The proposed RPPAML data format hopes to standardize RPPA data. Standardization of data would result in diverse client applications being able to operate on the same set of data. Additionally, having data in a standard format would enable data dissemination and data analysis.