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J Immunol Methods. 2013 Sep 30;395(1-2):1-13. doi: 10.1016/j.jim.2013.06.001. Epub 2013 Jun 13.

A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling.

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Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, M2-C200, PO Box 19024, Seattle, WA 98109-1024, United States.


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.


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

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