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:

  1. retrieve raw fastq data and process them to derive gene counts
  2. assess quality at several levels (raw read quality, mapping quality, sample quality)
  3. perform a differential expression analysis
  4. 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

Semaine de référence

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