In silico and statistical analyses of epigenomic data with UNIX and R

To support molecular and cell biologists in their quest for autonomy when dealing with bio-informatics, bio-statistics, genomics or systems biology, Pr Sandrine Lagarrigue - supported by Agrocampus Ouest - started offering a highly multidisciplinary and modular workshop dedicated to biologists ten years ago. I joined the teaching staf in 2014 and organize since then 4 yearly training days on sequence bio-informatics and statistical analyses for genomic and epigenomic data.

The workshop dedicated to ChIP-seq analysis address the following topics:

  • Introduction to epigenome screening technologies (ChIP-seq, ATAC-seq, MNase-seq …)
  • Biases and noise in sequencing data
  • Introduction to UNIX environment and Bash scripting
  • Work on a cluster with job schedulers (SLURM and SGE)
  • Use parallel environments
  • Use genomic databases (Ensembl, UCSC)
  • Quality check of ChIP-seq data
  • Pre-processing and alignment of ChIP-seq data
  • Peak calling
  • Irreproducible discovery rate
  • Use of R Bioconductor for functional genomics
  • Normalization strategies for epigenomic assays (RPM, TMM, Lowess)
  • Functional enrichment for epigenomic assays
  • Motif enrichement analysis

Below, you will find slides from our last ChIP-seq workshop (in french).

Day 1

Day 2

Bioconductor guide for ChIP-seq analysis


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