Analysis of ChIP-seq Data with SeqMonk (IN-PERSON)

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Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a method used to identify binding sites for transcription factors, histone modifications and other DNA-binding proteins across the genome. In this course, we will cover the fundamentals of ChIP-seq data analysis, from raw data to downstream applications.

We will start with an introduction to ChIP-seq methods and cover the bioinformatic steps in processing ChIP-seq data. We will then introduce the use of the graphical program SeqMonk to explore and visualise your data. Finally, you will perform peak calling and perform differential enrichment analysis.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

• This course is aimed at researchers with no prior experience in the analysis of ChIP-seq data, who would like to get started in processing their data and perform downstream analysis and visualisation of their results.

These are recommended, although not essential:

• A working knowledge of the UNIX command line (course registration page).
  • If you are not able to attend this prerequisite course, please work through our Unix command line materials ahead of the course (up to section 6).
• Basic understanding of high-throughput sequencing technologies.
  • Watch this iBiology video for an excellent overview.

Number of sessions: 1

Bioinformatics, Functional genomics, Data visualisation, ChIP-seq, Data handling, Data mining,

During this course you will learn about:

• What is ChIP-seq and how it works
• The characteristics of ChIP sequencing libraries and its specific data properties
• How to process ChIP-seq data and perform quality control
• How to visualise and explore your data
• Peak calling theory and practice as well as differential binding analysis

After this course you should be able to:

• Describe the different steps involved in performing ChIP-seq data analysis
• Map your sequencing reads to a reference genome and perform post-mapping QC ready for downstream analysis
• Use the SeqMonk software for ChIP-seq data visualisation and exploration
• Perform de novo peak calling and recognise the distinction between narrow and broad peaks
• Perform differential enrichment analysis

Presentations, demonstrations and practicals

• Free for registered University of Cambridge students
• £ 60/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) 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.
• £ 60/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 120/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

1

• Introduction to working with UNIX and bash (IN-PERSON)
• Introduction to R for Biologists (IN-PERSON)
• Quality Control in Sequencing Experiments (ONLINE LIVE TRAINING)
• Analysis of bulk RNA-seq data (IN-PERSON)
• Analysis of DNA Methylation using Sequencing (IN-PERSON)
• Analysis of single cell RNA-seq data (IN-PERSON)