Statistics for Microbiome
1 Preface
Welcome to Statistics for Microbiome.
This book is written for students, early-career researchers, and anyone new to microbiome data analysis who wants a clear, hands-on approach to statistical methods.
I began building these notes while navigating my own learning journey in microbiome science. As a computational biologist working across multi-omics datasets, I realized that statistical concepts often feel abstract until you see them applied to real microbial data. My goal here is to make that bridge explicit — showing not just what a statistical method is, but how and why to use it in microbiome research.
What you’ll find in this book: - Step-by-step explanations of key statistical concepts, from distributions to multivariate models
- R-based code examples with microbiome datasets
- Interpretation tips that connect outputs back to biological meaning
- Common pitfalls and how to avoid them in microbiome analysis
What this book is not:
This is not a theoretical statistics textbook. It is a curated collection of practical, reproducible notes, grounded in my personal experience, and aimed at helping you build confidence in applying statistics to microbiome data.
How to use this book: - Start at the beginning if you are new to statistics - Skip ahead to specific chapters if you need a refresher or targeted method - Run the code examples alongside the text to reinforce your understanding
When I first entered the microbiome field, I was overwhelmed by the amount of statistical terminology, conflicting analysis pipelines, and hidden assumptions buried in methods.
I remember wishing for a single, well-organized resource that explained just enough theory to make sense of the results, while still being fully reproducible with microbiome datasets.
This book is my attempt to create that resource, something I would have loved to have on my desk when I was starting out. If it saves you hours of confusion, prevents one misinterpretation, or sparks your curiosity to explore statistics more deeply, then it has done its job.
Shri Vishalini Rajaram