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

作者：Imholte Greg C; Sauteraud Renan; Korber Bette; Bailer Robert T; Turk Ellen T; Shen Xiaoying; Tomaras Georgia D; Mascola John R; Koup Richard A; Montefiori David C; Gottardo Raphael^*

来源：Journal of Immunological Methods, 2013, 395(1-2): 1-13.

DOI：10.1016/j.jim.2013.06.001

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

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 nonspecific 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.

• 出版日期2013-9-30
• 单位NIH; Los Alamos