wiSDOM: A visual and statistical analytics for interrogating microbiome

Shih Chi Su, James E. Galvin, Shun Fa Yang, Wen Hung Chung, Lun Ching Chang

Research output: Contribution to journalArticlepeer-review

Abstract

Motivation: We proposed a wiSDOM (web-based inclusionary analysis Suite for Disease-Oriented Metagenomics) R Shiny application which comprises six functional modules: (i) initial visualization of sampling effort and distribution of dominant bacterial taxa among groups or individual samples at different taxonomic levels; (ii) statistical and visual analysis of α diversity; (iii) analysis of similarity (ANOSIM) of β diversity on UniFrac, Bray-Curtis, Horn-Morisita or Jaccard distance and visualizations; (iv) microbial biomarker discovery between two or more groups with various statistical and machine learning approaches; (v) assessment of the clinical validity of selected biomarkers by creating the interactive receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC) for binary classifiers; and lastly (vi) functional prediction of metagenomes with PICRUSt or Tax4Fun. Results: The performance of wiSDOM has been evaluated in several of our previous studies for exploring microbial biomarkers and their clinical validity as well as assessing the alterations in bacterial diversity and functionality. The wiSDOM can be customized and visualized as per users' needs and specifications, allowing researchers without programming background to conduct comprehensive data mining and illustration using an intuitive browser-based interface.

Original languageEnglish (US)
Pages (from-to)2795-2797
Number of pages3
JournalBioinformatics
Volume37
Issue number17
DOIs
StatePublished - Sep 1 2021

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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