ArticleScientific reports2022
Integrative web cloud computing and analytics using MiPair for design-based comparative analysis with paired microbiome data.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- MiCML: a causal machine learning cloud platform for the analysis of treatment effects using microbiome profiles.BioData mining · 2025Article
- A unified web cloud computing platform MiMedSurv for microbiome causal mediation analysis with survival responses.Scientific reports · 2024Article
- MiTree: A Unified Web Cloud Analytic Platform for User-Friendly and Interpretable Microbiome Data Mining Using Tree-Based Methods.Microorganisms · 2023Article
- Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces.Biology methods & protocols · 2023Article
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Authors and funding
4 authors.
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Abstract
Pairing (or blocking) is a design technique that is widely used in comparative microbiome studies to efficiently control for the effects of potential confounders (e.g., genetic, environmental, or behavioral factors). Some typical paired (block) designs for human microbiome studies are repeated measures designs that profile each subject's microbiome twice (or more than twice) (1) for pre and post treatments to see the effects of a treatment on microbiome, or (2) for different organs of the body (e.g., gut, mouth, skin) to see the disparity in microbiome between (or across) body sites. Researchers have developed a sheer number of web-based tools for user-friendly microbiome data processing and analytics, though there is no web-based tool currently available for such paired microbiome studies. In this paper, we thus introduce an integrative web-based tool, named MiPair, for design-based comparative analysis with paired microbiome data. MiPair is a user-friendly web cloud service that is built with step-by-step data processing and analytic procedures for comparative analysis between (or across) groups or between baseline and other groups. MiPair employs parametric and non-parametric tests for complete or incomplete block designs to perform comparative analyses with respect to microbial ecology (alpha- and beta-diversity) and taxonomy (e.g., phylum, class, order, family, genus, species). We demonstrate its usage through an example clinical trial on the effects of antibiotics on gut microbiome. MiPair is an open-source software that can be run on our web server ( http://mipair.micloud.kr ) or on user's computer ( https://github.com/yj7599/mipairgit ).
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