Nichenet for analysis of cell-cell communication
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
