Monday - Classes from 2 to 8 pm Berlin time. Introduction to epigenomics, and 3D organisation of genomes

Lecture 1

  • Epigenomics introduction
  • Hi-C protocol
  • General processing of Hi-C data


Lab 1

  • Step-by-step processing of Hi-C data and integration with snakemake.
  • Use of existing Hi-C processing pipelines and common formats.
  • Manipulation and visualisation of sparse matrices using the cooler package



Tuesday: Application and analysis of Hi-C data

Lecture 2

  • Applications of Hi-C data (Scaffolding, 3D QTL, regulatory genomics)
  • Common analysis on Hi-C contact maps and their biological interpretation



  • Compute interpretable metrics on the Hi-C contact maps from previous lesson
  • Use existing methods for signal detection in Hi-C data.
  • Compare the signals across samplesVisualization techniques for Hi-C derived signals in jupyter notebook



Wednesday: 2-8 pm Berlin time. ChIP-seq analysis

Lecture 3

  • Introduction to ChIP-SeqMain uses of ChIP-Seq
  • General processing of ChIP-seq data
  • Introduction to Bioconductor


Lab 3

  • Step-by-step processing of ChIP-Seq data
  • Identification of TF-binding site or epigenomic histone modification using ChIP-seq peak calling
  • Identification of motifs and motif enrichment analysis
Thursday: 2-8 pm Berlin time. ATAC-seq
Lecture 4
  • Notion of local chromatin accessibility
  • Assays to measure chromatin accessibility: a long story of nucleases
  • Why peak callers should be carefully chosen
Lab 4
  • Identification of ATAC-seq peaks on multiple samples using YAPC
  • Differential binding analysis and clustering of ATAC-seq peaks
  • Study of chromatin accessibility at promoters with V-plots


Friday: 2-8 pm Berlin time. Integration and visualization of different genomics data

Lecture 5


  • Types of questions: Classification, description, differential analysis
  • Regulatory states from histone marks
  • Identification of transcription factor target genes using RNA-seq and ChIP-seq


Lab 5

  • Crossing results from ATAC-seq with chromHMM
  • Integration of ChIP-seq data and RNA-seq data
  • Analysis with external databases: GO analysis, protein functional interactions, ...