Oeiras
Portugal
High-throughput technologies such as next generation sequencing (NGS) can routinely produce massive amounts of data. These technologies allow us to describe all variants in a genome or to detect the whole set of transcripts that are present in a cell or tissue. However, such datasets pose new challenges in the way the data have to be analyzed, annotated and interpreted which are not trivial and are daunting to the wet-lab biologist. This course covers state-of-the-art and best-practice tools for NGS RNA-seq and ChIP-seq data analysis, which are of major relevance in today's genomic and gene expression studies.
The course is aimed at motivated wet-lab biologists who want to gain more of an understanding of NGS data and eventually progress to analysing their own data.
Participants should be already familiar with the R programming language. There will be a short recap of the key concepts at the beginning of the course; however it is expected that trainees are familiar with how to read data into R, perform basic subset operations and produce simple plots. Some introductory statistics, such as summary statistics for continuous data (mean, variance etc) and interpreting the results of a t-test, will be also be assumed. See "Statistics at Square One"" Chapters 1, 2, 3 and 7 (Statistics at Square One - BMJ) for a good overview. Basic unix skills, such as being able to list the contents of a directory and copy files, would also be an advantage. See "Session 1" of the Software Carpentry training for a Unix introduction (Shell-novice material from the Software Carpentry Foundation).
Registration deadline: 20 March 2016