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

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Imholte, GC; Sauteraud, R; Korber, B; Bailer, RT; Turk, ET; Shen, X; Tomaras, GD; Mascola, JR; Koup, RA; Montefiori, DC; Gottardo, R

Published Date

  • September 30, 2013

Published In

Volume / Issue

  • 395 / 1-2

Start / End Page

  • 1 - 13

PubMed ID

  • 23770318

Pubmed Central ID

  • PMC3999921

Electronic International Standard Serial Number (EISSN)

  • 1872-7905

Digital Object Identifier (DOI)

  • 10.1016/j.jim.2013.06.001


  • eng

Conference Location

  • Netherlands