In this course we will explore the use of modern bioinformatic tools that allow researchers to use pangenomes as their reference system when engaging in studies of organisms of all types. Such techniques will aid any researcher working on organisms of high genetic diversity or on organisms lacking a high-quality reference genome. This course targets all researchers interested in learning about an exciting paradigm shift in computational genomics.

This course is targeted for Biostatistical techniques often employed in analytical tools for high throughput data and multivariate data. Participants can expect to attend a thorough set of lectures that will reveal the conceptual frameworks that are needed to understand the methods. Extensive hands-on practice will be the main vehicle for providing the skills and user independence. To keep things in context, the course is exclusively based on biological examples.

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.

A Practical Workshop will be held during 7-11 May 2018, in Oeiras, hosted by the Portuguese ELIXIR Node in cooperation with the nodes involved in ELIXIR-EXCELERATE Workpackage 6 “Marine Metagenomics”.

In this five-day course we will introduce the main concepts that underlie many of the models that are frequently used in population genetics. We will focus on the importance of demographic history (e.g. effective sizes and migration patterns) in shaping genetic data. We will go through the basic notions that are central to population genetics, insisting particularly on the statistics used to measure genetic diversity and population differentiation. The course will also cover a short introduction to coalescent theory, Bayesian inference in population genetics and data simulation. We will also introduce methods that have been recently developed to analyse genomic data such as the PSMC method of Li and Durbin that reconstructs the demographic history of a species or population with the genome of a single individual.

Mass spectrometry based proteomic experiments generate ever larger datasets and, as a consequence, complex data interpretation challenges. In this course, the concepts and methods required to tackle these challenges will be introduced, covering peptide and protein identification, quantification, and differential analysis. Moreover, more advanced experimental designs and blocking will also be introduced. The core focus will be on shotgun proteomics data, and quantification using label-free precursor peptide (MS1) ion intensities. The course will rely exclusively on free and user-friendly software, all of which can be directly applied in your lab upon returning from the course. You will also learn how to submit data to PRIDE/ProteomeXchange, which is a common requirement for publication in the field, and how to browse and reprocess publicly available data from online repositories. The course will thus provide a solid basis for beginners, but will also bring new perspectives to those already familiar with standard data interpretation procedures in proteomics.

We will steer the participants into good practices in data management and work on practical examples taken from published papers and data, showing how these practices influence replicability and reproducibility. At the end we will discuss publication bias and its consequences in current research quality.

The BioData.pt | ELIXIR PT infrastructure and the Instituto Gulbenkian de Ciência (IGC) are proud to announce that a Data Carpentry Workshop, with a special focus on Genomics data, will be held at the IGC on October 15th and 16th 2018.

Mass spectrometry based proteomic experiments generate ever larger datasets and, as a consequence, complex data interpretation challenges. In this course, the concepts and methods required to tackle these challenges will be introduced, covering peptide and protein identification, quantification, and differential analysis. Moreover, more advanced experimental designs and blocking will also be introduced. The core focus will be on shotgun proteomics data, and quantification using label-free precursor peptide (MS1) ion intensities. The course will rely exclusively on free and user-friendly software, all of which can be directly applied in your lab upon returning from the course. You will also learn how to submit data to PRIDE/ProteomeXchange, which is a common requirement for publication in the field, and how to browse and reprocess publicly available data from online repositories. The course will thus provide a solid basis for beginners, but will also bring new perspectives to those already familiar with standard data interpretation procedures in proteomics.

Open Access Publishing & Managing and Sharing Research Data.