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Integrative web cloud computing and analytics using MiPair for design-based comparative analysis with paired

Hyojung Jang1, Hyunwook Koh2, Won Gu1

  • 1Department of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.

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|November 28, 2022
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Summary
This summary is machine-generated.

MiPair is a new web tool for analyzing paired microbiome data, essential for controlling confounders in comparative studies. It offers user-friendly, step-by-step analysis for microbial ecology and taxonomy in human microbiome research.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Pairing or blocking is crucial for controlling confounders in comparative microbiome studies.
  • Existing tools lack specialized support for paired microbiome data analysis.
  • Paired designs are common in human microbiome research, including repeated measures for treatment effects or different body sites.

Purpose of the Study:

  • Introduce MiPair, an integrated web-based tool for comparative analysis of paired microbiome data.
  • Provide a user-friendly platform for step-by-step data processing and analysis of paired microbiome samples.
  • Facilitate comparative analyses across groups or between baseline and other conditions.

Main Methods:

  • MiPair is a web cloud service offering parametric and non-parametric tests for complete or incomplete block designs.
  • The tool supports comparative analyses of microbial ecology (alpha- and beta-diversity) and taxonomic profiles.
  • Demonstrates usage with a clinical trial analyzing antibiotic effects on gut microbiome.

Main Results:

  • MiPair enables design-based comparative analysis specifically for paired microbiome data.
  • The tool addresses the gap in available web-based resources for paired microbiome study analysis.
  • Successfully applied in an example clinical trial for analyzing microbiome changes.

Conclusions:

  • MiPair provides a valuable, open-source solution for analyzing paired microbiome data.
  • The web tool enhances the usability and accessibility of comparative microbiome analysis.
  • Facilitates robust microbiome research by supporting paired study designs.