rapmad: Robust analysis of peptide microarray data

BMC Bioinformatics

Methodology Article

Ulf Reimer¹  Yvonne Kühne²  Ugur Sahin²  Martin Löwer²  John C Castle²  Özlem Türeci²  Andrée Rothermel²  Bernhard Y Renard³ 

[1] JPT Peptide Technologies GmbH, 12489, Berlin, Germany;The Institute for Translational Oncology and Immunology (TrOn), 55131, Mainz, Germany;The Institute for Translational Oncology and Immunology (TrOn), 55131, Mainz, Germany;Research Group Bioinformatics (NG 4), Robert Koch-Institute, 13353, Berlin, Germany;

关键词: Peptide;    Random Forest;    Antibody Concentration;    Random Forest Classifier;    Peptide Array;   

DOI  :  10.1186/1471-2105-12-324

 received in 2011-05-07, accepted in 2011-08-04,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundPeptide 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.ResultsWe 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.Conclusionsrapmad 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.

【 授权许可】

Unknown   
© Renard et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.