Training

The course covers analysis of NGS data. Using ChIP-Seq and RNA-Seq datasets as an example, the course will provide ideas and practical advice for the interpretation of NGS data sets in a genomic context.

Topics will include: RNA-Seq and ChIP-Seq data handling, quality assessment and visualisation; region identification and differential expression; data integration and external databases (ENCODE); statistical analysis using R/bioconductor.

What will I learn?

Lectures will give insight into how biological knowledge can be generated from NGS data and illustrate different ways of analysing and integrating such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of NGS data under the guidance of the lecturers and teaching assistants.

Familiarity with the technology and biological use cases of NGS is required, as is prior experience with standard RNA-Seq and/or ChIP-Seq workflows. Knowledge of R/Bioconductor and the Unix/Linux operating system are also required.

Is it right for me?

This course is aimed at advanced PhD students and post-doctoral researchers who are already applying next generation sequencing (NGS) technologies and bioinformatics methods in their research.

The aim of this course is to familiarise the participants with advanced data analysis methodologies for the interpretation and integration of data derived from different NGS applications including RNA-seq, ChIP-seq, DNA-methylation sequencing, genome-wide association studies (GWAS) and DNA variant detection.