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使用MiMed在用户友好的网页界面上进行综合微生物组因果中介分析。

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

作者信息

Jang Hyojung, Park Solha, Koh Hyunwook

机构信息

Department of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.

出版信息

Biol Methods Protoc. 2023 Oct 4;8(1):bpad023. doi: 10.1093/biomethods/bpad023. eCollection 2023.

Abstract

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).

摘要

将微生物组视为一种介导因子,其可将环境、行为或医学暴露传递至健康或疾病结局,明确微生物组在此过程中所起的作用是人类微生物组研究的核心目标。然而,中介分析的应用并未达到应有的程度。一个原因是缺乏用于微生物组中介分析(MiMed)的精心规划的程序、编译器和自动化计算系统,以执行一系列数据处理、多样性计算、数据归一化、下游数据分析和可视化。各学科的许多研究人员(如临床医生、公共卫生从业者和生物学家)也不熟悉命令行界面上的相关统计方法和编程语言。因此,在本文中,我们介绍了一个名为MiMed的网络云计算平台,该平台可在用户友好的网络界面上实现全面的MiMed。MiMed的主要特点如下。首先,MiMed可以在不同层面上对微生物组进行调查:(i)使用不同的生态指标(如α-和β-多样性指数)将其作为一个整体的微生物生态系统进行调查,或(ii)使用不同的数据归一化方法将其作为单个微生物分类群(如门、纲、目、科、属和种)进行调查。其次,MiMed能够进行协变量调整分析,以控制潜在的混杂因素(如年龄和性别),这对于增强结果的因果关系至关重要,尤其是对于观察性研究。第三,MiMed在中介效应估计和显著性检验方面都能够进行广泛的统计推断。第四,MiMed提供灵活且易于使用的数据处理和分析模块,并创建美观的图形表示。最后,MiMed利用ChatGPT通过人工智能技术搜索关于作为中介被显著发现的微生物分类群的已知信息。为了演示目的,我们将MiMed应用于研究口腔微生物组在电子烟吸烟与牙龈炎症之间龈下生态位中的中介作用。MiMed可在我们的网络服务器(http://mimed.micloud.kr)上免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a948/10576642/def0668b78ba/bpad023f1.jpg

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