MTGO-SC is an adaptation for single cell RNA-sequencing (scRNA-seq) of MTGO, a biological network module detection algorithm. MTGO-SC integrates external gene annotations, such as the Gene Ontology terms or Reactome pathways with the gene expression networks obtained from single-cell DGE matrices.
The typical scRNA-seq pipeline is designed to group cells into meaningful clusters, representing cells of similar (sub)type or stare. MTGO-SC provides the opportunity for a further step in the analysis by extracting the gene interaction network from each cluster, and detecting the gene functional modules. Each module is labeled with an annotation from the source provided by the user (for example, Reactome pathways). MTGO-SC is designed to be integrated with Seurat, a toolkit for single cell data analysis.
A practical example of application on MCA cluster, along with enrichment and term literature search, is provided in the Vignette.
Nazzicari, Nelson, Danila Vella, Claudia Coronnello, Dario Di Silvestre, Riccardo Bellazzi, and Simone Marini. "MTGO-SC, a tool to explore gene modules in single-cell RNA sequencing data." Frontiers in genetics (2019): 953.
- (main developer) Nelson Nazzicari - nelson DOT nazzicari AT crea DOT gov DOT it
- Simone Marini - simone DOT marini AT ufl DOT edu
- Danila Vella - dvella AT fondazionerimed DOT com