5.00 credits
30.0 h + 30.0 h
Q2
This learning unit is not open to incoming exchange students!
Teacher(s)
Branders Vincent;
Language
French
Prerequisites
- Molecular biology
- Biochemistry
- Data visualization
- Statistics
The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
This course will cover the different biological analysis techniques that generate high-throughput data (so-called “omics” techniques), such as: DNA and RNA sequencing, proteomics, metabolomics... (non-exhaustive list which will be adapted according to the rapid evolution of this field).
For each method, the course will introduce:
Finally, the course will include an introduction to the databases that can be used in this field (TCGA, GEO, Encode etc).
For each method, the course will introduce:
- The operating principle of each method (sequencing, mass spectrometry, etc.)
- Analysis, processing and normalization of raw data
- Data interpretation and visualization.
- The biases and pitfalls related to these techniques (problems of technical and biological variability, reproducibility, experimental design).
Finally, the course will include an introduction to the databases that can be used in this field (TCGA, GEO, Encode etc).
Learning outcomes
At the end of this learning unit, the student is able to : | |
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Content
1. Introduction
2. DNA sequencing (genomics)
6. Single Cell
2. DNA sequencing (genomics)
- Principle and technologies available
- Genome, exome, panel
- Analysis of raw data (alignment, reference genome, construction of a new genome, calling of variants, quality controls, etc.)
- Interpretation
- Principle and technologies
- Gene expression analysis
- Variants, mergers, new transcripts
- Mass spectrometry, principle and technologies
- Data analysis (identification of peptides and proteins, quantification)
- Data interpretation
6. Single Cell
Teaching methods
Lectures and guided practical session
- Practical sessions are performed in groups to use databases and results interpretation tools
Evaluation methods
The final grade consists of
The final exam is, by default, a written exam (on paper or, when appropriate, on a computer).
- 25% for practical sessions occurring during the semester
- 75% for the final exam
The final exam is, by default, a written exam (on paper or, when appropriate, on a computer).
Online resources
Teaching materials
- Required teaching material include all documents (lecture slides, project assignments, complements, ...) available from the Moodle website for this course.
- Les supports obligatoires sont constitués de l'ensemble des documents (transparents des cours magistraux, énoncés des travaux pratiques, compléments, ...) disponibles depuis le site Moodle du cours.
Faculty or entity
SINC
