Advanced ChIP-seq data analysis

PrerequisitesNew

The primary aim of this course is to familiarise participants with the analysis of ChIP-seq data and provide hands-on training on the latest analytical approaches.

The course starts with an introduction to ChIP-seq experiments and discusses quality control issues. We first show basic analytical steps such as alignment, peak calling and motif analysis, followed by practical examples on how to work with biological replicates and fundamental quality metrics for ChIP-seq datasets. We then focus on the analysis of differential binding when comparing between different samples. In addition, there is a short introduction to ATAC-seq data analysis for the detection of regions of open chromatin.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• Please be aware that these courses are only free for University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here.
• Further details regarding eligibility criteria are available here

• Basic understanding of high-throughput sequencing technologies
• Basic experience of command line UNIX. Sufficient UNIX experience might be obtained from one of the many UNIX tutorials available online.
• Basic knowledge of the R syntax. For a real beginner's introduction into R see here. More advanced R instructions can be found at Quick-R or An Introduction to R

Number of sessions: 2

Bioinformatics, Epigenomics, Functional genomics, Data visualisation, Data handing, Data mining, ChIP-seq,

After this course you should be able to:

• Perform alignment and peak calling of ChIP-seq datasets
• Assess the quality of your ChIP-seq datasets and reproducibility of replicates
• Compare samples by performing differential binding analysis
• Detect regions of open chromatin by analysing ATAC-seq datasets

During this course you will learn about:

• Considerations on experiment design for ChIP-seq
• Quality control of raw reads: FASTQC and fastx toolkit
• Read alignment to a reference genome: Bowtie
• File format conversion and processing: UCSC tools, wiggletools and samtools
• Peak calling: MACS2
• Motif analysis: MEME
• ChIP-seq quality check: ChIPQC and deepTools
• Working with biological replicates: IDR
• Differential binding analysis: DiffBind
• Analyse ATAC-seq data:

Presentations, demonstrations and practicals

• Free for University of Cambridge students
• £ 50/day for all University of Cambridge staff, including postdocs, and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 100/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

2

2 times a year

• Introduction to high-throughput sequencing data analysis
• Analysis of RNA-seq data with Bioconductor
• Analysis of small RNA-seq data
• Analysis of single cell RNA-seq data (IN-PERSON)
• Analysis of DNA Methylation using Sequencing (IN-PERSON)
• Introduction to genome variation analysis using NGS