Teacher(s)
Language
English
Content
This bioinformatics and high throughput biology data analysis course teaches how to analyse contemporary omics data using open source tools such as R/Bioconductor packages. At the end of the course, students will be in a position to analyse omics experiments, including raw data processing, quantitative data transformation and normalisation, and the statistical analysis and interpretation thereof.
This omics data analysis course will focus on the following themes:
- Raw data processing, including high throughput sequencing and mass spectrometry data.
- Omics data quality control.
- Quantitative data transformation and normalisation.
- Statistical data analysis.
- Omics data annotation.
- Omics data and project management and reproducible research.
This omics data analysis course will focus on the following themes:
- Raw data processing, including high throughput sequencing and mass spectrometry data.
- Omics data quality control.
- Quantitative data transformation and normalisation.
- Statistical data analysis.
- Omics data annotation.
- Omics data and project management and reproducible research.
Teaching methods
The course will be composed of practical sessions, during which the students will analyse omics data using R, RStudio, Bioconductor packages and command line tools. Students will also present their results as individual and/or group reports. Course attendance to all sessions (volume 1 and 2) is mandatory.
Evaluation methods
The students will be evaluated based on the presentations and reports they will prepare during the year and a final oral exam.
Online resources
The course material is available online: https://uclouvain-cbio.github.io/WSBIM2122/
Teaching materials
- Cours en ligne et informations complémentaires sur moodle. Obligatoires.
Faculty or entity
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Biomedicine
Master [120] in Statistics: Biostatistics
Master [120] in Chemistry and Bioindustries
Master [120] in Computer Science and Engineering
Master [120] in Computer Science