376-1347-00L Bioinformatic Approaches to Regulatory Genomics and Epigenomics
| Semester | Spring Semester 2023 |
| Lecturers | P.‑L. Germain |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Abstract | Epigenomics offers a genome-wide perspective on how changes in chromatin regulate gene expression and cellular phenotype. This course introduces the underlying biological notions through a hands-on exploration of such data, providing an introduction to (R-based) tools necessary to explore, visualize and interpret it. | |||||||||||||||||||||||||||||||||
| Learning objective | The objective of the course is two-fold: 1) to enable students, if not to be wholly independent with respect to NGS chromatin data analysis, at least to be able to autonomously explore, visualize and interpret such data; 2) to understand and critically appraise, from a genomics perspective and through hands-on data exploration, the key concepts underlying chromatin regulation of transcription and its impact on various biological phenomena. | |||||||||||||||||||||||||||||||||
| Content | - Introduction to the Bioconductor ecosystem for genomic data analysis, with a focus on flexible and re-usable tools (e.g. standard data structures and visualization techniques) - How to find and re-use data from the literature - Basic analysis pipelines for ATAC-seq, ChIP-seq, and related assays, with a focus on data manipulation, exploration and visualization, motif analysis, etc. (Single-cell ATAC-seq is presented but not included in the practicals) - Introduction to regulatory genomics, with critical discussions of some of its conceptual issues: types of functional elements, the histone code, sequence recognition and binding specificity, transcriptor factor (TF) activation and binding, DNA accessibility, topological domains and chromatin loops, etc. - Importance of chromatin regulation in differentiation and neurological conditions | |||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Familiarity with R (as can be obtained from statistics courses, dedicated R courses, or some bioinformatic courses); some basic bioinformatics knowledge is beneficial but not required. Students bring their own computer to run the analyses (in case of old computers, please contact the teachers to evaluate the need for an alternative solution). | |||||||||||||||||||||||||||||||||
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