Analysis of Microbiome Data

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

The microbiome represents a hidden world of tiny organisms populating not only our surroundings but also our own bodies. By enabling comprehensive profiling of these invisible creatures, modern genomic sequencing tools have given us an unprecedented ability to characterize these populations and uncover their outsize impact on our environment and health. Statistical analysis of microbiome data is critical to infer patterns from the observed abundances. The application and development of analytical methods in this area require careful consideration of the unique aspects of microbiome profiles. We begin this review with a brief overview of microbiome data collection and processing and describe the resulting data structure. We then provide an overview of statistical methods for key tasks in microbiome data analysis, including data visualization, comparison of microbial abundance across groups, regression modeling, and network inference. We conclude with a discussion and highlight interesting future directions.

Original languageEnglish (US)
Pages (from-to)483-504
Number of pages22
JournalAnnual Review of Statistics and Its Application
Volume11
Issue number1
DOIs
StatePublished - Apr 22 2024

Keywords

  • compositional data
  • differential abundance
  • network inference
  • ordination
  • regression modeling
  • zero inflation

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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