Date: No date given

Duration: P1DT7H

Language of instruction: English

Today it is possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). These scRNA-seq datasets can provide information about which cell types are present within a tissue and how they may potentially interact with each other. However, deciphering cell-cell communication from these datasets requires dedicated computational methods, such as NicheNet. The training combines demonstrations and hands-on exercises in R. You will practice NicheNet analysis on an example dataset. 

Keywords: Artificial Inteligence, omics

Learning objectives:

  • “Cover the most recent analysis features from NicheNet-v2”
  • “Discuss how to analyze cell-cell communication from scRNA-seq data via the NicheNet analysis framework”
  • “Highlight the benefits and limitations of NicheNet compared to other approaches and guide you in applying NicheNet to your datasets”
  • “Show how to analyze intercellular communication in multi-sample multi-condition scRNA-seq datasets with MultiNicheNet”

Organizer: VIB (https://ror.org/03xrhmk39)

Event types:

  • Workshops and courses


Activity log