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Functional genomic data analysis : transcriptomics


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Master in Life Science, ENS
Bio-M2_E02 | Functional genomic data analysis : transcriptomics
Year and Semester : M2 | S1
Where : ENS Biology Department, 3rd floor
Duration : 1 week | 30 hours (including personal work)
First and last day of class : September 5th-9th, 2022
Hours : 9:30-12:30 | 13:30-16:30
Maximum class size : 18-23 students

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 report at the end of the week.

Course material

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)
Claire Lansonneur (École normale supérieure, Paris)