What is GDA?
A three day theoretical and practical course on Genomic Data Analysis.

What is this course for?
Questions such as How can I find the causative mutation of the disease in this family? or What pathways are activated in my RNA-seq experiment? are becoming more frequent as Next Generation Sequencing (NGS) technologies are increasingly used in the laboratory. The International Course of Genomic Data Analysis has been designed to provide the researchers with the skills and tools to address these questions and many other ones related. The whole course is composed of two hands-on courses that focus on the analysis of Genomic variation and Transcriptomics, respectively, of Next Generation Sequencing Data. Both courses are complementary and can be attended independently or as a unique course.

The Genomic variation course reviews the different NGS technologies and their applications as well as the computational requirements of NGS-based projects. Following an introduction to NGS of genomes, exomes and panels, attendants will learn about NGS data quality issues, data pre-processing, how to compare sequenced reads with a reference genome and how to visualize the results in a genomic context. Then, the main aspects of genomic variant annotation, detection and prioritization of candidate variants will be covered. State-of-the-art software to assist in gene prioritization process will be used. Finally, NGS in the clinic will be reviewed with the use of panels of genes for precision diagnostic and the management of variants of uncertain effect.

The Transcriptomics course is devoted to transcriptomic studies (RNA-seq and miRNA-seq). After an introduction to NGS of transcriptomes, the attendants will learn to perform all the preprocessing steps to convert NGS reads into gene expression measurements. Then, gene expression data will be used to determine differential expression, to cluster expression patterns, or for building predictors. Functional profiling methodologies will be used to interpret the results according to gene ontology enrichment, network analysis, etc. Finally, sophisticated methods for pathwayanalysis of transcriptome profiles will be demonstrated. The Babelomics suite, a well-known package of gene expression analysis, will be used to illustrate.

By the end of the course, participants will have acquired skills to interpret NGS data and to use multiple software tools for genetic variant detection and for transcriptomic studies..

Who is the target audience?
The course is oriented to experimental researchers, post-doctoral and Ph.D. students in the field of Molecular Biology, Biotechnology, Medicine, Clinic, Bioinformatics and related disciplines who want to gain acquaintance with Next Generation Sequencing Data Analysis.

Why attending this course?
NGS technologies are greatly contributing to the development of omics studies. Nevertheless, it is a non-trivial task to transform the vast amount of data obtained with high-throughput sequencers into useful information. Thus, NGS data analysis is still a major bottleneck for most researchers in this field. The ability of correctly interpreting NGS results, as well as knowledge on the intrinsic properties of these data are essential to avoid incorrect experimental designs and the application of inappropriate analysis methodologies.

The aim of this course is to make researchers familiar with NGS data and to initiate them in the analysis pipeline by providing them hands-on training on analytical methodologies.


  • Computational Genomics Department

Dates and venue