Bioinformatic Analysis of RNA-sequencing
BIO-693 / 3 credits
Teacher(s): Burns Allison Marie, Guex Nicolas Jean Philippe, Iseli Christian, Jan Maxime, Mhalla Ep Marchand Linda
Language: English
Frequency
Every year
Summary
This course will take place from 3rd to 7th June 2024. It will introduce the workflows and techniques that are used for the analysis of bulk and single cell RNA-seq data. It will empower students to understand and analyze their own data.
Content
By day (5 days 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’s 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
- Gene ontology analysis
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: 24 students. More or less 6 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/
In the programs
- Number of places: 25
- Exam form: Oral presentation (session free)
- Subject examined: Bioinformatic Analysis of RNA-sequencing
- Lecture: 80 Hour(s)
- Exercises: 80 Hour(s)