Cargando…

Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces

It is a central goal of human microbiome studies to see the roles of the microbiome as a mediator that transmits environmental, behavioral, or medical exposures to health or disease outcomes. Yet, mediation analysis is not used as much as it should be. One reason is because of the lack of carefully...

Descripción completa

Detalles Bibliográficos
Autores principales: Jang, Hyojung, Park, Solha, Koh, Hyunwook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10576642/
https://www.ncbi.nlm.nih.gov/pubmed/37840574
http://dx.doi.org/10.1093/biomethods/bpad023
_version_ 1785121159067467776
author Jang, Hyojung
Park, Solha
Koh, Hyunwook
author_facet Jang, Hyojung
Park, Solha
Koh, Hyunwook
author_sort Jang, Hyojung
collection PubMed
description It is a central goal of human microbiome studies to see the roles of the microbiome as a mediator that transmits environmental, behavioral, or medical exposures to health or disease outcomes. Yet, mediation analysis is not used as much as it should be. One reason is because of the lack of carefully planned routines, compilers, and automated computing systems for microbiome mediation analysis (MiMed) to perform a series of data processing, diversity calculation, data normalization, downstream data analysis, and visualizations. Many researchers in various disciplines (e.g. clinicians, public health practitioners, and biologists) are not also familiar with related statistical methods and programming languages on command-line interfaces. Thus, in this article, we introduce a web cloud computing platform, named as MiMed, that enables comprehensive MiMed on user-friendly web interfaces. The main features of MiMed are as follows. First, MiMed can survey the microbiome in various spheres (i) as a whole microbial ecosystem using different ecological measures (e.g. alpha- and beta-diversity indices) or (ii) as individual microbial taxa (e.g. phyla, classes, orders, families, genera, and species) using different data normalization methods. Second, MiMed enables covariate-adjusted analysis to control for potential confounding factors (e.g. age and gender), which is essential to enhance the causality of the results, especially for observational studies. Third, MiMed enables a breadth of statistical inferences in both mediation effect estimation and significance testing. Fourth, MiMed provides flexible and easy-to-use data processing and analytic modules and creates nice graphical representations. Finally, MiMed employs ChatGPT to search for what has been known about the microbial taxa that are found significantly as mediators using artificial intelligence technologies. For demonstration purposes, we applied MiMed to the study on the mediating roles of oral microbiome in subgingival niches between e-cigarette smoking and gingival inflammation. MiMed is freely available on our web server (http://mimed.micloud.kr).
format Online
Article
Text
id pubmed-10576642
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-105766422023-10-15 Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces Jang, Hyojung Park, Solha Koh, Hyunwook Biol Methods Protoc Methods Article It is a central goal of human microbiome studies to see the roles of the microbiome as a mediator that transmits environmental, behavioral, or medical exposures to health or disease outcomes. Yet, mediation analysis is not used as much as it should be. One reason is because of the lack of carefully planned routines, compilers, and automated computing systems for microbiome mediation analysis (MiMed) to perform a series of data processing, diversity calculation, data normalization, downstream data analysis, and visualizations. Many researchers in various disciplines (e.g. clinicians, public health practitioners, and biologists) are not also familiar with related statistical methods and programming languages on command-line interfaces. Thus, in this article, we introduce a web cloud computing platform, named as MiMed, that enables comprehensive MiMed on user-friendly web interfaces. The main features of MiMed are as follows. First, MiMed can survey the microbiome in various spheres (i) as a whole microbial ecosystem using different ecological measures (e.g. alpha- and beta-diversity indices) or (ii) as individual microbial taxa (e.g. phyla, classes, orders, families, genera, and species) using different data normalization methods. Second, MiMed enables covariate-adjusted analysis to control for potential confounding factors (e.g. age and gender), which is essential to enhance the causality of the results, especially for observational studies. Third, MiMed enables a breadth of statistical inferences in both mediation effect estimation and significance testing. Fourth, MiMed provides flexible and easy-to-use data processing and analytic modules and creates nice graphical representations. Finally, MiMed employs ChatGPT to search for what has been known about the microbial taxa that are found significantly as mediators using artificial intelligence technologies. For demonstration purposes, we applied MiMed to the study on the mediating roles of oral microbiome in subgingival niches between e-cigarette smoking and gingival inflammation. MiMed is freely available on our web server (http://mimed.micloud.kr). Oxford University Press 2023-10-04 /pmc/articles/PMC10576642/ /pubmed/37840574 http://dx.doi.org/10.1093/biomethods/bpad023 Text en © The Author(s) 2023. Published by Oxford University Press. 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 Methods Article
Jang, Hyojung
Park, Solha
Koh, Hyunwook
Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces
title Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces
title_full Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces
title_fullStr Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces
title_full_unstemmed Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces
title_short Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces
title_sort comprehensive microbiome causal mediation analysis using mimed on user-friendly web interfaces
topic Methods Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10576642/
https://www.ncbi.nlm.nih.gov/pubmed/37840574
http://dx.doi.org/10.1093/biomethods/bpad023
work_keys_str_mv AT janghyojung comprehensivemicrobiomecausalmediationanalysisusingmimedonuserfriendlywebinterfaces
AT parksolha comprehensivemicrobiomecausalmediationanalysisusingmimedonuserfriendlywebinterfaces
AT kohhyunwook comprehensivemicrobiomecausalmediationanalysisusingmimedonuserfriendlywebinterfaces