A Computational Framework for the Analysis of Peptide Microarray Antibody Binding Data with Application to HIV Vaccine Profiling

Imholte et al., Journal of Immunological Methods (2013) - PMID: 23770318

Product(s) used in this publication:  PepStar™ Peptide Microarrays


We present an integrated analytical method for analyzing peptide microarray antibody binding data, from normalization through subject-specific positivity calls and data integration and visualization. Current techniques for the normalization of such data sets do not account for non-specific binding activity. A novel normalization technique based on peptide sequence information quickly and effectively reduced systematic biases. We also employed a sliding mean window technique that borrows strength from peptides sharing similar sequences, resulting in reduced signal variability. A smoothed signal aided in the detection of weak antibody binding hotspots. A new principled FDR method of setting positivity thresholds struck a balance between sensitivity and specificity. In addition, we demonstrate the utility and importance of using baseline control measurements when making subject-specific positivity calls. Data sets from two human clinical trials of candidate HIV-1 vaccines were used to validate the effectiveness of our overall computational framework.

Copyright © 2013 Elsevier B.V. All rights reserved.


Antibodies; Normalization; Peptide microarrays; Positivity calls; Software; Visualization

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