Single Cell RNA Seq (ScRNA-Seq) analyzes with R


  • From Tuesday 21/05/2024 to Wednesday 22/05/2024
  • From Tuesday 12/11/2024 to Wednesday 13/11/2024


Aurélien Barré, Benjamin Dartigues


  • Learn how to assess and manipulate data from Single Cell RNA Seq experiment
  • Learn how to carry out a differential analysis at multiple levels
  • Learn how to integrate complementary data for Single Cell RNA Seq analysis (spatial, trajectory, cell communication, cell identification...)


This training will introduce in particular the Seurat library allowing the manipulation and analysis of single cell RNAseq data as well as the visualization of analysis results.

  • Reminders of the concepts of Single Cell RNA Seq sequencing
  • Importing Single Cell data into R
  • Multiple Single Cell Data Integration
  • Quality Check and data pre-processing
  • Data normalization
  • Identification of markers
  • Clustering and cell assignment
  • Differential analysis of cell groups
  • Know how to integrate spatialization data
  • Know how to integrate trajectory data
  • Know how to integrate cellular communication data
  • Know how to integrate epigenetic data (ATAC-seq)


Mastery of the R language.

Have taken the "Language R: Introduction" course or equivalent level.

In order to verify that your mastery of the R language is sufficient to be able to follow this course, we invite you to complete and return the downloadable test HERE


Engineers, biology technicians and training bioinformaticians

Anyone wishing to "exploit" NGS data or evaluate and reproduce the analyzes presented in scientific publications