Introduction to high-throughput sequencing data analysis

This course provides an introduction to high-throughput sequencing (HTS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply HTS technologies and bioinformatics methods in their research.

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

The course will include an introduction to Unix and R but to get the most out of the course we suggest acquiring:

• 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: 4

Bioinformatics, ChIP-seq, Data handling, Data mining, Data visualisation, Epigenomics, Functional genomics, RNA-seq, Sequence variations, Transcriptomics

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
• Perform alignment and peak calling of ChIP-seq datasets
• Perform alignment, quantification of expression and guided transcriptome assembly of RNA-seq datasets
• Understand the standard file formats for representing variant data
• Apply filters to your list of variants and functionally annotate variants

During this course you will learn about:

• HTS 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
• Analysis of variants

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

4 days

A number of times per year

• Introduction to RNA-seq and ChIP-seq 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 mapped NGS data with SeqMonk (ONLINE LIVE TRAINING)
• Introduction to genome variation analysis using NGS
• Variant Analysis with GATK