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

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...

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Detalles Bibliográficos
Autores principales: Hartman, Holly, Wang, Yuge, Schroeder, Harry W., Cui, Xiangqin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993274/
https://www.ncbi.nlm.nih.gov/pubmed/29883460
http://dx.doi.org/10.1371/journal.pone.0198528
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author Hartman, Holly
Wang, Yuge
Schroeder, Harry W.
Cui, Xiangqin
author_facet Hartman, Holly
Wang, Yuge
Schroeder, Harry W.
Cui, Xiangqin
author_sort Hartman, Holly
collection PubMed
description 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).
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spelling pubmed-59932742018-06-15 Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard Hartman, Holly Wang, Yuge Schroeder, Harry W. Cui, Xiangqin PLoS One Research Article 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). Public Library of Science 2018-06-08 /pmc/articles/PMC5993274/ /pubmed/29883460 http://dx.doi.org/10.1371/journal.pone.0198528 Text en © 2018 Hartman et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hartman, Holly
Wang, Yuge
Schroeder, Harry W.
Cui, Xiangqin
Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard
title Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard
title_full Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard
title_fullStr Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard
title_full_unstemmed Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard
title_short Absorbance summation: A novel approach for analyzing high-throughput ELISA data in the absence of a standard
title_sort absorbance summation: a novel approach for analyzing high-throughput elisa data in the absence of a standard
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993274/
https://www.ncbi.nlm.nih.gov/pubmed/29883460
http://dx.doi.org/10.1371/journal.pone.0198528
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