Open Access Methodology article

rapmad: Robust analysis of peptide microarray data

Bernhard Y Renard12, Martin Löwer1, Yvonne Kühne1, Ulf Reimer3, Andrée Rothermel1, Özlem Türeci1, John C Castle1* and Ugur Sahin1

Author Affiliations

1 The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany

2 Research Group Bioinformatics (NG 4), Robert Koch-Institute, 13353 Berlin, Germany

3 JPT Peptide Technologies GmbH, 12489 Berlin, Germany

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BMC Bioinformatics 2011, 12:324  doi:10.1186/1471-2105-12-324

Published: 4 August 2011

Abstract

Background

Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel analysis of thousands of peptides in a single run they are suitable for high-throughput settings. Since data characteristics of peptide microarrays differ from DNA oligonucleotide microarrays, computational methods need to be tailored to these specifications to allow a robust and automated data analysis. While follow-up experiments can ensure the specificity of results, sensitivity cannot be recovered in later steps. Providing sensitivity is thus a primary goal of data analysis procedures. To this end we created rapmad (Robust Alignment of Peptide MicroArray Data), a novel computational tool implemented in R.

Results

We evaluated rapmad in antibody reactivity experiments for several thousand peptide spots and compared it to two existing algorithms for the analysis of peptide microarrays. rapmad displays competitive and superior behavior to existing software solutions. Particularly, it shows substantially improved sensitivity for low intensity settings without sacrificing specificity. It thereby contributes to increasing the effectiveness of high throughput screening experiments.

Conclusions

rapmad allows the robust and sensitive, automated analysis of high-throughput peptide array data. The rapmad R-package as well as the data sets are available from http://www.tron-mz.de/compmed webcite.