Introduction to RNA-seq and ChIP-seq data analysis

The aim of this course is to familiarize the participants with the primary analysis of datasets generated through two popular high-throughput sequencing (HTS) assays: ChIP-seq and RNA-seq.

This course starts with a brief introduction to the transition from capillary to high-throughput sequencing (HTS) and discusses quality control issues, which are common among all HTS datasets. Next, we will present the alignment step and how it differs between the two analysis workflows. Finally, we focus on dataset specific downstream analysis, including peak calling and motif analysis for ChIP-seq and quantification of expression, transcriptome assembly and differential expression analysis for RNA-seq.

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 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, Transcriptomics, Data handing, Data mining, ChIP-seq, RNA-seq,

After this course you should be able to:

• Understand the advantages and limitations of the high-throughput assays presented
• Assess the quality of your datasets
• Understand the difference between splice-aware and splice-unaware aligners
• Perform alignment and peak calling of ChIP-seq datasets
• Perform alignment, quantification of expression and guided transcriptome assembly of RNA-seq datasets

During this course you will learn about:

• High-throughput sequencing technology
• Quality control of raw reads: FASTQC and fastx toolkit
• Considerations on experiment design for ChIP-seq and RNA-seq
• Read alignment to a reference genome: Bowtie and Tophat
• File format conversion and processing: UCSC tools and samtools
• Peak calling: MACS
• Motif analysis: MEME
• Quantification of expression and guided transcriptome assembly: Cufflinks
• Differential expression analysis: Cuffdiff

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 days

3 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