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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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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. |
format | Online Article Text |
id | pubmed-10070037 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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