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iMAP: an integrated bioinformatics and visualization pipeline for microbiome data analysis.

Teresia M Buza1,2, Triza Tonui3, Francesca Stomeo3,4

  • 1The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, State College, PA, USA. ndelly@gmail.com.

BMC Bioinformatics
|July 5, 2019
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Summary

The Integrated Microbiome Analysis Pipeline (iMAP) simplifies microbiome research by integrating bioinformatics analysis and visualization. This user-friendly tool enhances data interpretation and reproducibility for microbial community studies.

Keywords:
16S rRNA geneBioinformatics pipelineMicrobial communityMicrobiome bioinformaticsMicrobiome data analysisMicrobiome data visualizationPhylogenetic analysisPhylogenetic annotation

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) generates vast microbiome data, posing challenges for biological interpretation.
  • Existing bioinformatics tools often require advanced programming skills and in-depth knowledge of their implementation.
  • Reproducibility, repeatability, and result provenance are critical yet often unmet needs in microbiome research.

Purpose of the Study:

  • To develop a user-friendly and portable bioinformatics tool for integrated microbiome analysis and data visualization.
  • To address the complexity and time-consuming nature of microbiome data processing.
  • To enhance the accessibility of advanced microbiome analysis for researchers.

Main Methods:

  • Developed iMAP (Integrated Microbiome Analysis Pipeline), a wrapper tool.
  • Integrated functionalities for metadata profiling, read quality control, sequence processing, and classification.
  • Utilized Mothur or QIIME2 for microbial community profiling, R packages for graphics, and R-markdown for reports.
  • Implemented a review-as-you-go (RAYG) approach for web-based progress reports.

Main Results:

  • iMAP provides a comprehensive pipeline for microbiome analysis, from raw reads to diversity analysis.
  • The tool integrates bioinformatics analysis with data visualization, simplifying complex data interpretation.
  • Web-based progress reports generated via RAYG allow for progressive review of intermediate outputs.

Conclusions:

  • iMAP offers a streamlined and integrated solution for microbiome data analysis.
  • The pipeline ensures high-quality results through in-depth quality control, enhancing conclusion accuracy.
  • Vibrant visuals and progressive reporting facilitate a better understanding of complex microbiome data.