How to read this book – Epigenomics Data Analysis with EpiNexus

The parts

Foundations (Chapters 1–3): what each assay measures, how to design an experiment that can answer your question, and which data and reference files you need.
From reads to peaks (Chapters 4–8): how reads are processed, checked, turned into peaks and shown as signal tracks.
Comparing conditions (Chapters 9–10): differential analysis and spike-in normalisation.
From regions to biology (Chapters 11–13): from regions to genes, pathways, motifs and enhancers.
Case studies (Chapters 14–17): one public dataset per assay, analysed from start to finish.
Reporting (Chapters 18–19): results that others can reproduce, and how to solve problems.

You can read the chapters in order or one at a time. Each chapter starts with the question it answers.

Boxes

Best practice

What published standards or benchmarks recommend, with the source. Where no publication sets a value, the box ends by saying what EpiNexus uses instead: a sensible default, not evidence.

Pitfall

A common mistake and how to avoid it.

In EpiNexus 1.2

How to do the step in EpiNexus, for the version named. These boxes are short because the interface changes. The method around them does not.

The example datasets

Table 1: Datasets used as examples.

Assay	Dataset	Study
ChIP-seq (H3K27ac)	GEO GSE155100	Boogerd et al. (2023)
DNA methylation (RRBS; neurons without the enzymes Dnmt3a and Dnmt3b)	GEO GSE167954	Zocher et al. (2021)
ATAC-seq (SOX2 removal in mouse embryonic stem cells)	GEO GSE209527	Maresca et al. (2023)
CUT&Tag (H3K27me3 in mouse spermatogonia, with a fly spike-in)	GEO GSE221942	Hu et al. (2024)
CUT&RUN (the transcription factor MafB in mouse macrophages)	GEO GSE287346	Vanneste et al. (2026)

Using EpiNexus

During its pilot phase, EpiNexus is available on request. Write to info@epinexus.io to ask for an account. You do not need an account to follow the book: every example shows its results.