Network analysis of large-scale ImmGen and Tabula Muris datasets highlights metabolic diversity of tissue mononuclear phagocytes

GAM-clustering provides metabolic variability within dataset using a novel network-based computational approach that utilizes cellular transcriptional profiles as proxies. The metabolic network of reactions from KEGG database is presented as a graph that has vertices corresponding to metabolites and the edges corresponding to the reactions with the expressed genes. In the graph the method tries to find a set of connected subgraphs, with each corresponding well to a certain gene expression pattern. Curret analysis reveals the major metabolic features associated with different subpopulations and highlights a number of metabolic modules that are specific to individual cell types, tissues of residence, or developmental stages.

To explore data please visit the following links:

ImmGen MNP OS (GSE122108)

• Interactive gene expression heatmap in Phantasus (top 12,000 genes)
• Interactive gene expression heatmap in Phantasus (all genes)
• PCA with samples annotation
• Interactive heatmap of metabolic modules in Phantasus
• Interactive Cytoscape session of metabolic modules

ImmGen Phase1 (GSE15907)

• Interactive gene expression heatmap in Phantasus (MNP subset; top 12,000 genes)
• Interactive gene expression heatmap in Phantasus (MNP subset; all genes)
• Interactive gene expression heatmap in Phantasus (all samples; all genes)

Tabula Muris Senis

• Interactive gene expression plot in Single-cell Navigator (myeloid subset)

How to cite this article: Gainullina A. et al. Network analysis of large-scale ImmGen and Tabula Muris datasets highlights metabolic diversity of tissue mononuclear phagocytes, Cell Reports, Volume 42, Issue 2, 2023, 112046, https://doi.org/10.1016/j.celrep.2023.112046.

GitHub repository contains the basic scripts and data analysis example. The user friendly R-package is coming soon.