Bioinformatic Analysis of RNA-sequencing
BIO-693 / 3 crédits
Enseignant(s): Burns Allison Marie, Guex Nicolas Jean Philippe, Iseli Christian, Jan Maxime, Mhalla Ep Marchand Linda
Langue: Anglais
Remark: The course is fully booked - no more registration possible
Frequency
Every year
Summary
This course will take place from 2nd to 6th June 2025 in room AAC 1 37. It introduces the workflows and techniques that are used for the analysis of bulk and single-cell RNA-seq data. It empowers students to understand and analyze their own data.
Content
By day (5 days in total):
1. Retrieving raw data from the facility and reference data onto a lab workstation or an HPC cluster and perform mapping
2. Understand the contents of the raw and mapped files, prepare summary data to export to a laptop
3. Get R going with the proper analysis packages on each student laptop, start the analysis of the retrieved data
4. Finalize the analysis, plus start analysis of a selected/assigned dataset per group of students
5. Each group of students prepares a report on their assigned dataset in the morning and presents their results in the afternoon
The course topics will include:
Day 1: Working with data at the command line
- A refresher of bash and R scripting
- Tips and tricks for data reproducibility
Day 2: Sequencing alignments
- Downloading and aligning raw RNA-seq data on HPC clusters
- Quality assessment of sequenced and aligned files
Day 3: Bulk RNA-sequencing workflows
- Getting read counts per gene
- Data quality assessment
- Differential expression analysis and visualization
Day 4: Single cell RNA-sequencing workflows
- Filtering and normalizing single cell datasets
- Cell clustering and cell type assignments
- Differential expression analysis and visualization
Day 5: Prepare and present reports of independent student analysis performed in teams
Learning Outcomes
By the end of this course, you should be able to:
- retrieve raw fastq data and process them to derive gene counts
- assess quality at several levels (raw read quality, mapping quality, sample quality)
- perform a differential expression analysis
- gather functional annotation and emit hypotheses on interpreting the resultsBy day (5 days total)
Note
Maximum number of participants: 30 students. More or less 15 slots will be kept for interested UNIL doctoral students.
This course is not open to free auditors.
Keywords
genomics, bulk RNA-seq, single cell RNA-seq
Learning Prerequisites
Required courses
None
Assessment methods
Oral presentation
Resources
Bibliography
Website: https://bix.unil.ch/
Dans les plans d'études
- Nombre de places: 30
- Forme de l'examen: Exposé (session libre)
- Matière examinée: Bioinformatic Analysis of RNA-sequencing
- Cours: 80 Heure(s)
- Exercices: 80 Heure(s)
- Type: optionnel
- Nombre de places: 30
- Forme de l'examen: Exposé (session libre)
- Matière examinée: Bioinformatic Analysis of RNA-sequencing
- Cours: 80 Heure(s)
- Exercices: 80 Heure(s)
- Type: optionnel