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CytokineExplore: An Online Tool for Statistical Analysis of Cytokine Concentration Datasets

PURPOSE: Cytokine data sets are increasing both in the number of different cytokines measured and the number of samples assayed. Further, typically data from different groups may be contrasted, eg, normal vs complication subjects. Many univariate and multivariate statistical techniques exist to stud...

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Autores principales: Kassem, Osama, Al-Saleh, Abdulwahab, Azizieh, Fawaz, Dingle, Kamaludin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406373/
https://www.ncbi.nlm.nih.gov/pubmed/32801833
http://dx.doi.org/10.2147/JIR.S253255
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author Kassem, Osama
Al-Saleh, Abdulwahab
Azizieh, Fawaz
Dingle, Kamaludin
author_facet Kassem, Osama
Al-Saleh, Abdulwahab
Azizieh, Fawaz
Dingle, Kamaludin
author_sort Kassem, Osama
collection PubMed
description PURPOSE: Cytokine data sets are increasing both in the number of different cytokines measured and the number of samples assayed. Further, typically data from different groups may be contrasted, eg, normal vs complication subjects. Many univariate and multivariate statistical techniques exist to study such cytokine datasets, but the ability to implement these techniques may be lacking for some practitioners, or may not be available quickly and conveniently. Here, we introduce CytokineExplore, an online tool for multi-cytokine and multi-group data analysis of user-provided Microsoft Excel data files. MATERIALS AND METHODS: In order to illustrate the tool features, we use data from intrauterine growth retardation (IUGR), a pregnancy complication, and normal healthy subjects as a control. The dataset contains levels for 10 cytokines, namely: IL-4, IL-6, IL-8, IL-10, IL-12, IL-13, IL-18, IL-23, interferon-gamma (IFN-γ) and tumour necrosis-alpha (TNF-α), obtained from 34 women with IUGR (further divided into 17 symmetric and 17 asymmetric cases) and 24 gestationally age-matched normal controls. RESULTS: The online tool automatically generates box-plots, histograms, PCA and PLSDA plots, t-tests and Mann–Whitney statistical tests, cytokine importance values for separating two groups, heatmaps for comparing multiple groups, and other functionalities. Figures generated can be directly downloaded for use in presentations or journal articles. CONCLUSION: The tool facilitates quick and easy numerical exploration and multivariate analysis of cytokine datasets, to aid basic understanding and hypothesis generation.
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spelling pubmed-74063732020-08-14 CytokineExplore: An Online Tool for Statistical Analysis of Cytokine Concentration Datasets Kassem, Osama Al-Saleh, Abdulwahab Azizieh, Fawaz Dingle, Kamaludin J Inflamm Res Original Research PURPOSE: Cytokine data sets are increasing both in the number of different cytokines measured and the number of samples assayed. Further, typically data from different groups may be contrasted, eg, normal vs complication subjects. Many univariate and multivariate statistical techniques exist to study such cytokine datasets, but the ability to implement these techniques may be lacking for some practitioners, or may not be available quickly and conveniently. Here, we introduce CytokineExplore, an online tool for multi-cytokine and multi-group data analysis of user-provided Microsoft Excel data files. MATERIALS AND METHODS: In order to illustrate the tool features, we use data from intrauterine growth retardation (IUGR), a pregnancy complication, and normal healthy subjects as a control. The dataset contains levels for 10 cytokines, namely: IL-4, IL-6, IL-8, IL-10, IL-12, IL-13, IL-18, IL-23, interferon-gamma (IFN-γ) and tumour necrosis-alpha (TNF-α), obtained from 34 women with IUGR (further divided into 17 symmetric and 17 asymmetric cases) and 24 gestationally age-matched normal controls. RESULTS: The online tool automatically generates box-plots, histograms, PCA and PLSDA plots, t-tests and Mann–Whitney statistical tests, cytokine importance values for separating two groups, heatmaps for comparing multiple groups, and other functionalities. Figures generated can be directly downloaded for use in presentations or journal articles. CONCLUSION: The tool facilitates quick and easy numerical exploration and multivariate analysis of cytokine datasets, to aid basic understanding and hypothesis generation. Dove 2020-07-31 /pmc/articles/PMC7406373/ /pubmed/32801833 http://dx.doi.org/10.2147/JIR.S253255 Text en © 2020 Kassem et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Kassem, Osama
Al-Saleh, Abdulwahab
Azizieh, Fawaz
Dingle, Kamaludin
CytokineExplore: An Online Tool for Statistical Analysis of Cytokine Concentration Datasets
title CytokineExplore: An Online Tool for Statistical Analysis of Cytokine Concentration Datasets
title_full CytokineExplore: An Online Tool for Statistical Analysis of Cytokine Concentration Datasets
title_fullStr CytokineExplore: An Online Tool for Statistical Analysis of Cytokine Concentration Datasets
title_full_unstemmed CytokineExplore: An Online Tool for Statistical Analysis of Cytokine Concentration Datasets
title_short CytokineExplore: An Online Tool for Statistical Analysis of Cytokine Concentration Datasets
title_sort cytokineexplore: an online tool for statistical analysis of cytokine concentration datasets
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406373/
https://www.ncbi.nlm.nih.gov/pubmed/32801833
http://dx.doi.org/10.2147/JIR.S253255
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