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Bioinformatics Advance Access originally published online on April 27, 2006
Bioinformatics 2006 22(14):1760-1766; doi:10.1093/bioinformatics/btl162
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Identification of humoral immune responses in protein microarrays using DNA microarray data analysis techniques

Suman Sundaresh 1,2, Denise L. Doolan 4,5, Siddiqua Hirst 3, Yunxiang Mu 3, Berkay Unal 3, D. Huw Davies 3, Philip L. Felgner 3 and Pierre Baldi 1,2,*

1 School of Information and Computer Sciences, University of California Irvine, CA, USA
2 Institute for Genomics and Bioinformatics and, University of California Irvine, CA, USA
3 Center for Virus Research, University of California Irvine, CA, USA
4 Naval Medical Research Center, Silver Spring MD, USA
5 Department of Molecular Microbiology and Immunology, School of Hygiene and Public Health, Johns Hopkins University Baltimore, MD, USA

*To whom correspondence should be addressed.

Motivation: We present a study of antigen expression signals from a newly developed high-throughput protein microarray technique. These signals are a measure of antibody–antigen binding activity and provide a basis for understanding humoral immune responses to various infectious agents and supporting vaccine and diagnostic development.

Results: We investigate the characteristics of these expression profiles and show that noise models, normalization, variance estimation and differential expression analysis techniques developed in the context of DNA microarray analysis can be adapted and applied to these protein arrays. Using a high-dimensional dataset containing measurements of expression profiles of antibody reactivity against each protein (295 antigens and 9 controls) in 42 malaria (Plasmodium falciparum) protein arrays derived from 22 donors with various clinical presentations of malaria, we present a methodology for the analysis and identification of significantly expressed antigens targeted by immune responses for individual sera, groups of sera and across stages of infection. We also conduct a short study highlighting the top immunoreactive antigens where we identify three novel high priority antigens for future evaluation.

Availability: All software programs (in R) used for the analysis described in this paper are freely available for academic purposes at www.igb.uci.edu/servers/servers.html

Contact: pfbaldi{at}uci.edu

Received on January 23, 2006; revised on April 16, 2006; accepted on April 23, 2006

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