Bioinformatics: Next Generation Sequencing data analysis

PrerequisitesNew

This course provides an introduction to next generation sequencing (NGS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and BS-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 BS-seq data under the guidance of the lecturers and teaching assistants.

Further information is available here.

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

• PhD students and post-doctoral researchers who are applying or planning to apply NGS technologies and bioinformatics methods in their research
• Booking priority is given to people from Cambridge University and Collaborating Institutes
• Individual Course fees are required only from External participants not from Collaborating Institutes

• 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: 3

• short read alignment
• data handling and visualisation
• region identification
• differential expression
• differential methylation
• data quality assessment and statistical analysis

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

Presentations, demonstrations and practicals

3

A number of times per year

• Bioinformatics: Analysing mapped NGS data with SeqMonk
• Bioinformatics: EMBL-EBI - Archives for Next Generation Sequence Data with the EBI
• Bioinformatics: Whole Exome Sequencing and RNA-sequence data analysis