BIO-603(LG) / 1 credit

Teacher: La Manno Gioele

Language: English

Remark: 3-day Block course, every year in January. To register, contact EDMS Administration


Every year


Give students a feel for how single-cell genomics datasets are analyzed from raw data to data interpretation. Different steps of the analysis will be demonstrated and the most common statistical and bioinformatic techniques applied by the students. Data analysis in single-cell genomics.


The students will be provided with a modest-sized single-cell transcriptomics raw dataset for without any biological context given initially. The students will learn how to use analysis tools and statistical methods to understand the biological process the dataset is capturing.
Starting from read-mapping, they will perform steps of data processing and quality control so to end up with a gene expression table.
On this data, the students will learn how to perform feature selection and data visualization. The combination of multivariate analysis routines and literature based search will lead to the an interpretation of the observed gene expression variation.


Please note that you are not allowed to inscribe in your own group!

Note that 3 practical courses are mandatory for all EDMS students and that they have the priority; each course has between 2 to 4 possible slots.

Therefore, please do not register by yourself to this course, this will be done by the EDMS program administrator!


single-cell, genomics, data analysis, transcriptomics

Learning Prerequisites

Required courses

A course that included python or R programming project.

Learning Outcomes

By the end of the course, the student must be able to:

  • Perform a basic analysis of a single cell RNA-seq dataset autonomously

Assessment methods

Project report



Butler et al, Nature Biotechnology, 2018


In the programs

  • Number of places: 4
  • Exam form: Project report (session free)
  • Subject examined: Practical - LaManno Lab
  • Lecture: 6 Hour(s)
  • Practical work: 18 Hour(s)
  • Type: mandatory

Reference week

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