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Seed: a user-friendly tool for exploring and visualizing microbial community data.

Daniel Beck1, Christopher Dennis1, James A Foster1

  • 1Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA.

Bioinformatics (Oxford, England)
|October 22, 2014
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Summary
This summary is machine-generated.

Simple Exploration of Ecological Data (Seed) is a new R-based tool for microbial community data analysis. It offers a user-friendly interface for exploring ecological datasets using various visualization and statistical methods.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Ecology

Background:

  • Microbial community data analysis requires accessible tools for exploration.
  • Existing methods may lack user-friendly interfaces for complex ecological datasets.

Purpose of the Study:

  • To introduce Simple Exploration of Ecological Data (Seed), a novel data exploration tool.
  • To provide a user-friendly interface for analyzing microbial community data.

Main Methods:

  • Seed is developed using the R programming language and the Shiny library.
  • It integrates powerful R-based statistical and visualization functions.
  • The tool supports principal coordinate analyses, scatter plots, bar plots, hierarchical clustering, and heatmaps.

Main Results:

  • Seed enables users to interactively explore ecological datasets.
  • It facilitates the application of advanced analytical techniques through a simple interface.

Conclusions:

  • Seed offers an accessible platform for microbial ecologists to explore their data.
  • The tool enhances data analysis capabilities through an intuitive user interface.