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omicplotR: visualizing omic datasets as compositions.

Daniel J Giguere1, Jean M Macklaim2, Brandon Y Lieng2

  • 1Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, N6A5C1, Canada. dgiguer@uwo.ca.

BMC Bioinformatics
|November 16, 2019
PubMed
Summary
This summary is machine-generated.

omicplotR offers a user-friendly graphical interface for exploring omics data, simplifying differential abundance analysis for researchers. This tool uses generalizable compositional methods for reproducible visualizations, aiding scientists without scripting experience.

Keywords:
Compositional dataData visualizationDifferential abundanceDifferential expressionEffect plotsExploratory data analysis

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics
  • Metagenomics

Background:

  • Differential abundance analysis is crucial for high-throughput sequencing data interpretation.
  • Existing software often requires command-line proficiency and may lack compositional validity.
  • Researchers need accessible tools for analyzing complex omics datasets.

Purpose of the Study:

  • To introduce omicplotR, a novel software tool for visual exploration of omics data.
  • To provide a user-friendly graphical interface for differential abundance analysis.
  • To enable researchers, regardless of scripting experience, to perform complex data visualizations.

Main Methods:

  • Development of omicplotR with a graphical user interface (GUI).
  • Implementation of generalizable compositional methods for data analysis.
  • Integration of reproducible visualization techniques such as PCA, hierarchical clustering, MA plots, and effect plots.

Main Results:

  • omicplotR facilitates visual exploration of omics datasets for users with varying technical skills.
  • The software generates reproducible visualizations including PCA, hierarchical clustering, MA plots, and effect plots.
  • Functionality demonstrated using a publicly available metatranscriptome dataset.

Conclusions:

  • omicplotR provides an accessible GUI for exploring sequence count data.
  • The tool employs generalizable compositional methods, enhancing visualization capabilities.
  • omicplotR empowers investigators without command-line experience to effectively visualize and interpret omics data.