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

Publication ,  Journal Article
Imholte, GC; Sauteraud, R; Korber, B; Bailer, RT; Turk, ET; Shen, X; Tomaras, GD; Mascola, JR; Koup, RA; Montefiori, DC; Gottardo, R
Published in: J Immunol Methods
September 30, 2013

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.

Duke Scholars

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Published In

J Immunol Methods

DOI

EISSN

1872-7905

Publication Date

September 30, 2013

Volume

395

Issue

1-2

Start / End Page

1 / 13

Location

Netherlands

Related Subject Headings

  • ROC Curve
  • Protein Interaction Mapping
  • Protein Array Analysis
  • Immunology
  • Immunologic Techniques
  • Humans
  • HIV-1
  • HIV Antigens
  • HIV Antibodies
  • Epitopes
 

Citation

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Imholte, G. C., Sauteraud, R., Korber, B., Bailer, R. T., Turk, E. T., Shen, X., … Gottardo, R. (2013). A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling. J Immunol Methods, 395(1–2), 1–13. https://doi.org/10.1016/j.jim.2013.06.001
Imholte, Greg C., Renan Sauteraud, Bette Korber, Robert T. Bailer, Ellen T. Turk, Xiaoying Shen, Georgia D. Tomaras, et al. “A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling.J Immunol Methods 395, no. 1–2 (September 30, 2013): 1–13. https://doi.org/10.1016/j.jim.2013.06.001.
Imholte GC, Sauteraud R, Korber B, Bailer RT, Turk ET, Shen X, et al. A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling. J Immunol Methods. 2013 Sep 30;395(1–2):1–13.
Imholte, Greg C., et al. “A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling.J Immunol Methods, vol. 395, no. 1–2, Sept. 2013, pp. 1–13. Pubmed, doi:10.1016/j.jim.2013.06.001.
Imholte GC, Sauteraud R, Korber B, Bailer RT, Turk ET, Shen X, Tomaras GD, Mascola JR, Koup RA, Montefiori DC, Gottardo R. A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling. J Immunol Methods. 2013 Sep 30;395(1–2):1–13.
Journal cover image

Published In

J Immunol Methods

DOI

EISSN

1872-7905

Publication Date

September 30, 2013

Volume

395

Issue

1-2

Start / End Page

1 / 13

Location

Netherlands

Related Subject Headings

  • ROC Curve
  • Protein Interaction Mapping
  • Protein Array Analysis
  • Immunology
  • Immunologic Techniques
  • Humans
  • HIV-1
  • HIV Antigens
  • HIV Antibodies
  • Epitopes