Academic as well as industrial research in molecular biology often involve high-throughput genomic technologies. Furthermore, large data collections of this type are publicly available, which can benefit new projects provided you can integrate them. Software tools and web sites exist that can perform some common analyses but it frequently happens that one needs specific analyses or graphical representations, which are not offered.
To address this need, a platform has emerged and is widely used: R and Bioconductor. R is a programming language and an interactive environment to analyze and explore data, and Bioconductor is an ensemble of R libraries to cover many bioinformatics problems.
The lecture will allow you to become autonomous by learning the basics of R and their applications in genomics. We will learn R language elements, data graphical exploration, common data processing such as transcriptomes or proteomes, as well as some elementary notions regarding interactomes. You will learn how to handle classical analyses that are necessary to many labs and most importantly to search for information and learn by yourself.
We will introduce and use some concepts of statistics (P-values, Q-values, etc.), but this lecture is not a statistics lecture. It will also not turn you in bioinformaticians but rather into biologists able to deal with basic analyses of genomic data. In case you do have knowledge in mathematics, statistics, or programming, you will benefit from them but this not required to attend the lecture.
- Enseignant: Villemin Jean Philippe