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Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard

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  • Holly Hartman
  • Yuge Wang
  • Harry W Schroeder Jr
  • Xiangqin Cui

Abstract

We have developed a very simple method, termed absorbance summation (AS), for comparing protein concentrations between samples in ELISA assays without a standard. This method sums the observed absorbance values from all dilutions to obtain one data point for each sample to be used for comparison. AS is less computationally intensive than fitting sigmoidal curves, and it avoids the difficulty of parameter estimation for samples with absorbance values lying primarily at the lower tail of the curve. Our simulation studies showed that it performs much better than the sigmoidal curve fitting method and the conventional endpoint titer method. The power of this simple method is as high as the formal curve fitting followed by the estimation of area under the curve (AUC).

Suggested Citation

  • Holly Hartman & Yuge Wang & Harry W Schroeder Jr & Xiangqin Cui, 2018. "Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-12, June.
    • Handle: RePEc:plo:pone00:0198528
    DOI: 10.1371/journal.pone.0198528
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    References listed on IDEAS

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    1. Andrew Gelman & Ginger L. Chew & Michael Shnaidman, 2004. "Bayesian Analysis of Serial Dilution Assays," Biometrics, The International Biometric Society, vol. 60(2), pages 407-417, June.
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    1. Michael Pigula & Yen-Chung Lai & Minseob Koh & Christian S. Diercks & Thomas F. Rogers & David A. Dik & Peter G. Schultz, 2024. "An unnatural amino acid dependent, conditional Pseudomonas vaccine prevents bacterial infection," Nature Communications, Nature, vol. 15(1), pages 1-9, December.

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