Analysis of Differential Expression with RNAseq (first course in 2019)

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   IMPORTANT DATES for this Course
   Deadline for applications: May 31st 2019
   Course dates: June 3rd - June 7th 2019

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. In 2019, he moved to UCIBIO FCT-NOVA to develop his scientific independence, and focus on projects related to cellular diversity in health and disease, towards more translatable biomedical research.

Affiliation: UCIBIO, Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, Caparica, 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

Daniel Neves is a bioinformatics specialist at the Bioinformatics Unit (UBI) at IGC. He has a bachelor's degree in Computer Engineering, and a MSc degree in Computational Biology from Faculdade de Ciências da Universidade de Lisboa (Lisboa, Portugal). In his MSc project, that was supervised by Luisa Figueiredo and Nuno Barbosa-Morais at Instituto de Medicina Molecular (Lisboa, Portugal), he used RNA-seq to unveil the circadian clock of Trypanosoma brucei, an ancient human pathogen. He has significant experience in Next Generation Sequencing (NGS) data analysis, having collaborated in the design and analysis of a wide variety of transcriptomics, epigenetics and genomics experiments. He is particularly interested in how visualization can help understand large datasets, avoid mistakes and uncover relevant information. At the IGC, he is currently responsible for providing consultancy and bioinformatics support within the infrastructure.

Affiliation: Instituto Gulbenkian de Ciência, Oeiras, PT

Course description


High-throughput technologies allow us to detect transcripts in a cell or tissue. This course covers practical aspects of the analysis of differential gene expression by RNAseq, from planning the gathering of sequence data to the generation of tables of differentially expressed gene lists and visualization of results. We will also explore some specificities of single-cell RNAseq data analysis. Towards the end, we will cover some of the initial steps of secondary analysis, such as functional enrichment of the gene lists. Participants will start by learning the concepts using small example datasets, and then will apply the same methodology in real-world problems in the training room. At the end of the course, participants will be able to apply the learned methods to their own data, with a high degree of autonomy.

Target Audiences

Life Scientists who want to be able to use NGS data (RNAseq) to infer genes differentially expressed between different conditions. Computational researchers that wish to get acquainted with the concepts and methodologies used in RNAseq are also welcome.


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:  May 23rd 2019