Introduction to ChIP-seq Data Analysis and Visualisation using Ensembl


to be determined


The King's Buildings, The University of Edinburgh, Edinburgh, Scotland, UK

Application deadline:

to be determined

Cancellation deadline:

to be determined


12 (selection of applicants)

Registration fee:

to be determined


Bert Overduin

ChIP-seq (Chromatin ImmunoPrecipitation followed by Sequencing) is a popular high-throughput sequencing assay to identify binding sites of DNA-associated proteins and histone modifications. Determining how proteins interact with DNA and the epigenetic landscape is essential for elucidating the regulation of gene expression. The aim of this workshop is to familiarise the participants with the primary analysis of ChIP-seq data sets by providing a balanced set of lectures and practicals on analysis methodologies. Practicals include publicly available ChIP-seq datasets, processed using widely used and open-source software programs (e.g. FASTQC, BWA, samtools, bedtools, wiggletools, MACS2, MEME, TOMTOM, ngsplot) and visualised on the Ensembl genome browser.

"Very well presented and the presenters were so knowledgeable and helpful." (July 2015)


Dr. Myrto Kostadima (Ensembl Regulation Project Leader, European Bioinformatics Institute, Hinxton, Cambridge, UK)

*This workshop is made possible by the free of charge contribution of the Ensembl team *

Workshop format

The workshop consists of presentations, demos and hands-on tutorials.

Who should attend

Graduates, postgraduates, and PIs, who are using, or planning to use, ChIP-seq technology in their research and want to learn how to process and analyse ChIP-seq data.


A general understanding of molecular biology and genomics, and elementary skills in computer usage are required.

Covered topics

High-throughput sequencing technology
Considerations on experiment design for ChIP-seq
Quality control of raw reads: FASTQC and fastx toolkit
Read alignment to a reference genome: BWA
File format conversion and processing: samtools and wiggletools
Peak calling: MACS2
Motif analysis: MEME
IDR analysis
Genome browser visualisation and trackhub generation: Ensembl