Analysis of Differential Expression with RNAseq

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   IMPORTANT DATES for this Course
   Deadline for applications: April 10th 2017
   Course dates: April 17th - April 20th 2017

Candidates with adequate profile will be accepted in the next 72 hours after the application, until we reach 20 participants.


Daniel Sobral graduated in Informatics Engineering from Instituto Superior Técnico (Lisbon, Portugal). His interest in Biology led him to join the Gulbenkian PhD programme, and conduct his doctoral studies in Bioinformatics at the Université Aix-Marseille (France) with Dr. Patrick Lemaire. During his PhD he worked in different aspects of bioinformatics, particularly focusing on gene expression networks underlying embryonic development of a model organism, all of this integrated into a community resource. Later he became a Developer for the Ensembl Project where he worked mostly in integrating epigenetic data from the ENCODE project in Ensembl. In this context he gained significant experience with high throuthput sequencing data. In 2012 he moved back to Portugal, where he joined the Bioinformatics Unit at the IGC to assist the local research community in handling the sequencing revolution brought about by high throughput technologies. Within this role he been collaborating in several projects, ranging from genomics, transcriptomics and epigenetics. He has become the Head of the Bioinformatics Unit at IGC since 2014.

Affiliation: Instituto Gulbenkian de Ciência, Oeiras, PT

Daniel Faria graduated in Biological Engineering from Instituto Superior Técnico (Lisboa, Portugal). His interest in Bioinformatics led him to pursue a PhD on that topic, at the Faculdade de Ciências da Universidade de Lisboa (Lisboa, Portugal) under Dr. André Falcão and Dr. António Ferreira, focusing on automated protein function prediction and on the usage and structure of the Gene Ontology. He developed applications for computing semantic similarity between genes and for enrichment analysis, based on the Gene Ontology. After his PhD, his research interests veered towards knowledge representation and integration in Biomedical Sciences, and particularly the topic of Ontology Matching. He remained at the Faculdade de Ciências as a post-doc to pursue this research topic, and became a leading expert on it by developping the tool AgreementMakerLight. In 2015, he joined the Bioinformatics Unit at the IGC as a post-doc on the EXCELERATE project, to work on the integration and annotation of plant phenomic data.

Affiliation: Instituto Gulbenkian de Ciência, Oeiras, PT

Mauro Truglio is Bioinformatics Specialist at the Bioinformatics Unit of the IGC. After his Master's degree he worked on developing software for Proteomics in two Universities in Rome; later he focused on NGS data analysis, working for NZGL (New Zealand's main NGS service provider) on a great variety of projects that range from genome assembly, to RNA-Seq, to metagenomics. At the IGC he is currently taking care of the development of tools and pipelines for analysis of NGS data, and providing bioinformatics support the Institute's research groups.

Affiliation: Instituto Gulbenkian de Ciência, Oeiras, PT

Course description


High-throughput technologies allow us to detect transcripts present in a cell or tissue. This course covers practical aspects of the analysis of differential gene expression by RNAseq. Participants will be presented with real world examples and work with them in the training room, covering all the steps of RNAseq analysis, from planning the gathering of sequence data to the generation of tables of differentially expressed gene lists and visualization of results. We we will also cover some of the initial steps of secondary analysis, such as functional enrichment of the obtained gene lists.

Target Audiences

Life Scientists who want to be able to use NGS data to evaluate gene expression (RNAseq). Computational researchers that wish to get acquainted with the concepts and methodologies used in RNAseq are also welcome. Participants are encouraged to bring their own data and will have the opportunity to apply the concepts learned in the course.


Familiarity with elementary statistics and a few basics of scripting in R.

Please have a look at the following resources and gauge your ability to use R in statitics at the basic level: Basic Unix command line skills, such as being able to navigate in a directory tree and copy files. See, for example, "Session 1" of the Software Carpentry training for a Unix introduction (Shell-novice material from the Software Carpentry Foundation).


Detailed Program

Instituto Gulbenkian de Ciência,

Apartado 14, 2781-901 Oeiras, Portugal

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Last updated:  Feb 21st 2017