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Explicet: graphical user interface software for metadata-driven management, analysis and visualization of microbiome

Charles E Robertson1, J Kirk Harris, Brandie D Wagner

  • 1Department of Molecular, Cellular and Developmental Biology, University of Colorado, Boulder, CO 80309, USA, University of Colorado Microbiome Research Consortium, Department of Pediatrics, University of Colorado Anschutz Medical Campus, Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO 80045, USA, Incubix Incorporated, Boulder, CO 80301, USA and Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.

Bioinformatics (Oxford, England)
|September 12, 2013
PubMed
Summary
This summary is machine-generated.

The Explicet software package offers a user-friendly way to combine microbiome analysis pipeline outputs with metadata. This tool enhances the visualization of microbial community data for researchers.

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Area of Science:

  • Microbiome research
  • Microbial community ecology
  • Bioinformatics
  • Data visualization

Background:

  • Microbiome studies are rapidly expanding, driven by advances in next-generation sequencing.
  • Several high-performance sequence analysis pipelines (e.g., QIIME, MOTHUR, VAMPS) are available for microbiome analysis.
  • A need exists for intuitive tools to integrate pipeline outputs with metadata for comprehensive analysis.

Purpose of the Study:

  • To introduce Explicet, a graphical user interface-based software package.
  • To provide a robust and intuitive solution for integrating microbiome analysis pipeline outputs with user-specified metadata.
  • To facilitate the visualization of combined microbiome and metadata for enhanced research insights.

Main Methods:

  • Development of a graphical user interface (GUI) for the Explicet software package.
  • Integration of outputs from established microbiome analysis pipelines (e.g., QIIME, MOTHUR, VAMPS).
  • Incorporation of user-specified metadata for combined data analysis and visualization.

Main Results:

  • Explicet successfully integrates data from various microbiome analysis pipelines.
  • The software provides an intuitive platform for combining analysis outputs with metadata.
  • Enhanced visualization capabilities allow for clearer interpretation of microbiome community data.

Conclusions:

  • Explicet addresses a critical need for a user-friendly tool in microbiome data analysis.
  • The software empowers researchers to effectively visualize and interpret complex microbiome datasets.
  • Explicet facilitates a more integrated approach to microbiome research, combining computational outputs with biological context.