Accèder directement au contenu

Functional genomic data analysis : transcriptomics


PDF - 62.1 ko
M2_IMaLiS_E02_HTSdataAnalysis Planning_2020_v1slc.pdf



Master in Life Science, ENS
Bio-M2_E02 | Functional genomic data analysis : transcriptomics
Year : 2 (M2)
Semester : 1 (S1)
Duration : 1 week

Coordination

Stéphane Le Crom (Sorbonne Université)

Credits

3 ECTS

Keywords

Functional Genomics, Transcriptomics, High Throughput Sequencing, Microarrays, Bioinformatics.

Course Prerequisites

Computer knowledge : bases in computer programming, practice of Linux command lines and knowledge of R language.

Course objectives and description

Aims : The aims of this teaching unit are to understand and handle various data format that are available from high throughput sequencing techniques in genomics. This course allows students to better appreciate the limits and drawbacks of high throughput genomics datasets.
Themes : This course introduces the high throughput sequencing techniques and the various applications available in genomics. It focuses on the analysis of gene expression studies and covers the most important bioinformatics and statistical concepts to delineate differentially expressed genes.
Computer-training sessions make use of open source software like R programming language, MeV (MultiExperiment Viewer) and IGV (Integrative Genomics Viewer).
The course covers the following fields : data quality analysis, read mapping on a reference genome, read alignment visualization, data normalization, statistical differential analysis, functional annotation and expression network visualization.
Organization : The course is organized over one week, with classes during the morning, computer-training sessions during the afternoon and free analysis workshop around datasets.

Assessment

Students will be evaluated based on a written exam at the end of the week.

Infrasctucture : The practicals will be conducted on the core cluster of the Institut Français de Bioinformatique. We kindly acknowledge the IFB for supporting this course.

Teaching team

Stéphane Le Crom (Sorbonne Université, Paris)
Florent Charton (École normale supérieure, Paris)
Claire Lansonneur (École normale supérieure, Paris)
Matthieu Moreau (École normale supérieure, Paris)