README.md

In ne1s0n/MTGOsc: MTGO analysis applied to Single Cell data

MTGO-SC

Extracting gene modules from single cell RNA-seq cell clusters

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.

A post-processing step after cell clustering

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.

Example of MTGO-SC application

A practical example of application on MCA cluster, along with enrichment and term literature search, is provided in the Vignette.

Citing MTGO-SC

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.

Developers

• (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

ne1s0n/MTGOsc documentation built on April 20, 2022, 9:35 p.m.