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pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations

OBJECTIVE: To enable interactive visualization of phenome-wide association studies (PheWAS) on electronic health records (EHR). MATERIALS AND METHODS: Current PheWAS technologies require familiarity with command-line interfaces and lack end-to-end data visualizations. pyPheWAS Explorer allows users...

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Detalles Bibliográficos
Autores principales: Kerley, Cailey I, Nguyen, Tin Q, Ramadass, Karthik, Cutting, Laurie E, Landman, Bennett A, Berger, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10070037/
https://www.ncbi.nlm.nih.gov/pubmed/37021295
http://dx.doi.org/10.1093/jamiaopen/ooad018
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author Kerley, Cailey I
Nguyen, Tin Q
Ramadass, Karthik
Cutting, Laurie E
Landman, Bennett A
Berger, Matthew
author_facet Kerley, Cailey I
Nguyen, Tin Q
Ramadass, Karthik
Cutting, Laurie E
Landman, Bennett A
Berger, Matthew
author_sort Kerley, Cailey I
collection PubMed
description OBJECTIVE: To enable interactive visualization of phenome-wide association studies (PheWAS) on electronic health records (EHR). MATERIALS AND METHODS: Current PheWAS technologies require familiarity with command-line interfaces and lack end-to-end data visualizations. pyPheWAS Explorer allows users to examine group variables, test assumptions, design PheWAS models, and evaluate results in a streamlined graphical interface. RESULTS: A cohort of attention deficit hyperactivity disorder (ADHD) subjects and matched non-ADHD controls is examined. pyPheWAS Explorer is used to build a PheWAS model including sex and deprivation index as covariates, and the Explorer’s result visualization for this model reveals known ADHD comorbidities. DISCUSSION: pyPheWAS Explorer may be used to rapidly investigate potentially novel EHR associations. Broader applications include deployment for clinical experts and preliminary exploration tools for institutional EHR repositories. CONCLUSION: pyPheWAS Explorer provides a seamless graphical interface for designing, executing, and analyzing PheWAS experiments, emphasizing exploratory analysis of regression types and covariate selection.
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spelling pubmed-100700372023-04-04 pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations Kerley, Cailey I Nguyen, Tin Q Ramadass, Karthik Cutting, Laurie E Landman, Bennett A Berger, Matthew JAMIA Open Application Notes OBJECTIVE: To enable interactive visualization of phenome-wide association studies (PheWAS) on electronic health records (EHR). MATERIALS AND METHODS: Current PheWAS technologies require familiarity with command-line interfaces and lack end-to-end data visualizations. pyPheWAS Explorer allows users to examine group variables, test assumptions, design PheWAS models, and evaluate results in a streamlined graphical interface. RESULTS: A cohort of attention deficit hyperactivity disorder (ADHD) subjects and matched non-ADHD controls is examined. pyPheWAS Explorer is used to build a PheWAS model including sex and deprivation index as covariates, and the Explorer’s result visualization for this model reveals known ADHD comorbidities. DISCUSSION: pyPheWAS Explorer may be used to rapidly investigate potentially novel EHR associations. Broader applications include deployment for clinical experts and preliminary exploration tools for institutional EHR repositories. CONCLUSION: pyPheWAS Explorer provides a seamless graphical interface for designing, executing, and analyzing PheWAS experiments, emphasizing exploratory analysis of regression types and covariate selection. Oxford University Press 2023-04-03 /pmc/articles/PMC10070037/ /pubmed/37021295 http://dx.doi.org/10.1093/jamiaopen/ooad018 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Application Notes
Kerley, Cailey I
Nguyen, Tin Q
Ramadass, Karthik
Cutting, Laurie E
Landman, Bennett A
Berger, Matthew
pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations
title pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations
title_full pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations
title_fullStr pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations
title_full_unstemmed pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations
title_short pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations
title_sort pyphewas explorer: a visualization tool for exploratory analysis of phenome-disease associations
topic Application Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10070037/
https://www.ncbi.nlm.nih.gov/pubmed/37021295
http://dx.doi.org/10.1093/jamiaopen/ooad018
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