Whole Transcriptome Data Analysis

Overview

Course Overview

This course will teach the biological researchers how to analyse biological data sets using open-source software. Most of the analysis will be performed with docker4seq package, which was developed to facilitate the use of computing demanding applications in the field of NGS data analysis. Docker4seq package uses docker containers that embed demanding computing tasks (e.g. short reads mapping) into isolated containers. This approach provides multiple advantages: the user does not need to install all the software on its local server, the results generated by different containers can be organised in pipelines and reproducible research is guarantee by the possibility of sharing the docker images used for the analysis.

Computers for hands-on exercises will be provided along with demo data sets.

Audience

This course was developed for biological researchers as the intended audience. Basic knowledge of massively parallel sequencing (MPS) is desirable, however R-coding skills and deep knowledge of statistics are not necessary.

Modules

• Tools for RNA-seq data analysis
• Experimental design
• Quality control
• Normalisation and data reformatting
• Basic statistics
• Selecting differentially regulated genes/microRNAs
• Selecting alternative splicing events
• Multiple testing
• Biological interpretation

Learning Outcomes

• Understand the importance of experimental design in order to ask sensible biological questions
• Assess the quality of your data
• Perform normalisation and reformatting procedures
• Complete basic statistical tests on Next Generation Sequencing (NGS) data
• Understand some of the problems encountered when analysing data

Speakers

Scientific Organisers and Speakers

Marco Beccuti

University of Turin

Italy

Vladimir Benes

EMBL Heidelberg

Germany

Raffaele Calogero

University of Turin

Italy

Course Organisers

Inna Boesselmann

EMBL Heidelberg

Germany

Programme