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

Summary: In this article we present Simple Exploration of Ecological Data (Seed), a data exploration tool for microbial communities. Seed is written in R using the Shiny library. This provides access to powerful R-based functions and libraries through a simple user interface. Seed allows users to explore ecological datasets using principal coordinate analyses, scatter plots, bar plots, hierarchal clustering and heatmaps. Availability and implementation: Seed is open source and available at https://github.com/danlbek/Seed. Contact: danlbek@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

• Publication year

  2014

• Venue

  Bioinform.

• Publication date

  2014-10-20

• Fields of study

  Biology, Medicine, Computer Science, Environmental Science

• Identifiers
  DOI 10.1093/bioinformatics/btu693PMID 25332377PMCID 4325548
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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