Project overview

Aim

Demonstrate key analytical steps and decision points in 16S rRNA amplicon sequencing data analysis, with emphasis on preprocessing choices, normalization strategies, and downstream visualization approaches.

Reusable Outputs

Reproducible R Markdown pipeline for microbiome data analysis, including preprocessing, statistical analysis, and visualisation. Designed for adaptation to new datasets and similar study designs.

Key insights
  • Microbiome analysis requires explicit decisions on preprocessing steps, including filtering of low-abundance and low-prevalence taxa.
  • Different normalization and transformation approaches (e.g. relative abundance, rarefaction) can substantially influence downstream interpretation.
  • Analytical outcomes depend on methodological choices rather than a single “correct” pipeline, making transparency in decision-making essential.
  • The tutorial emphasizes reproducible workflow design and the rationale behind common analytical choices in amplicon sequencing analysis.