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Assessment of Variability in the SOMAscan Assay
SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using t...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5660188/ https://www.ncbi.nlm.nih.gov/pubmed/29079756 http://dx.doi.org/10.1038/s41598-017-14755-5 |
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author | Candia, Julián Cheung, Foo Kotliarov, Yuri Fantoni, Giovanna Sellers, Brian Griesman, Trevor Huang, Jinghe Stuccio, Sarah Zingone, Adriana Ryan, Bríd M. Tsang, John S. Biancotto, Angélique |
author_facet | Candia, Julián Cheung, Foo Kotliarov, Yuri Fantoni, Giovanna Sellers, Brian Griesman, Trevor Huang, Jinghe Stuccio, Sarah Zingone, Adriana Ryan, Bríd M. Tsang, John S. Biancotto, Angélique |
author_sort | Candia, Julián |
collection | PubMed |
description | SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using the current 1.3 k assay, as well as the previous 1.1 k version. We discuss normalization procedures and examine different strategies to minimize intra- and interplate nuisance effects. We implement a meta-analysis based on calibrator samples to characterize the coefficient of variation and signal-over-background intensity of each protein analyte. By incorporating coefficient of variation estimates into a theoretical model of statistical variability, we also provide a framework to enable rigorous statistical tests of significance in intervention studies and clinical trials, as well as quality control within and across laboratories. Furthermore, we investigate the stability of healthy subject baselines and determine the set of analytes that exhibit biologically stable baselines after technical variability is factored in. This work is accompanied by an interactive web-based tool, an initiative with the potential to become the cornerstone of a regularly updated, high quality repository with data sharing, reproducibility, and reusability as ultimate goals. |
format | Online Article Text |
id | pubmed-5660188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-56601882017-11-01 Assessment of Variability in the SOMAscan Assay Candia, Julián Cheung, Foo Kotliarov, Yuri Fantoni, Giovanna Sellers, Brian Griesman, Trevor Huang, Jinghe Stuccio, Sarah Zingone, Adriana Ryan, Bríd M. Tsang, John S. Biancotto, Angélique Sci Rep Article SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using the current 1.3 k assay, as well as the previous 1.1 k version. We discuss normalization procedures and examine different strategies to minimize intra- and interplate nuisance effects. We implement a meta-analysis based on calibrator samples to characterize the coefficient of variation and signal-over-background intensity of each protein analyte. By incorporating coefficient of variation estimates into a theoretical model of statistical variability, we also provide a framework to enable rigorous statistical tests of significance in intervention studies and clinical trials, as well as quality control within and across laboratories. Furthermore, we investigate the stability of healthy subject baselines and determine the set of analytes that exhibit biologically stable baselines after technical variability is factored in. This work is accompanied by an interactive web-based tool, an initiative with the potential to become the cornerstone of a regularly updated, high quality repository with data sharing, reproducibility, and reusability as ultimate goals. Nature Publishing Group UK 2017-10-27 /pmc/articles/PMC5660188/ /pubmed/29079756 http://dx.doi.org/10.1038/s41598-017-14755-5 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Candia, Julián Cheung, Foo Kotliarov, Yuri Fantoni, Giovanna Sellers, Brian Griesman, Trevor Huang, Jinghe Stuccio, Sarah Zingone, Adriana Ryan, Bríd M. Tsang, John S. Biancotto, Angélique Assessment of Variability in the SOMAscan Assay |
title | Assessment of Variability in the SOMAscan Assay |
title_full | Assessment of Variability in the SOMAscan Assay |
title_fullStr | Assessment of Variability in the SOMAscan Assay |
title_full_unstemmed | Assessment of Variability in the SOMAscan Assay |
title_short | Assessment of Variability in the SOMAscan Assay |
title_sort | assessment of variability in the somascan assay |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5660188/ https://www.ncbi.nlm.nih.gov/pubmed/29079756 http://dx.doi.org/10.1038/s41598-017-14755-5 |
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