Identify TFs and their targets with immune functions via GSEA¶
By constructing GRNs, we have identified TFs with footprints on chromatin accessibility data and significant correlations with expression of target genes. Among these TFs, we further prioritized them by comparing their target size across cell types. The larger target size is, the regulation is more specific in one cell type than the rest. Now we want to know if marker TFs and their targets have any immune-related role in the regulation of each cell type.
Perform GSEA via WebGestaltR¶
Three methods available on the WebGestalt server:
- Over Representation Analysis (ORA) - Venn diagram
- Gene Set EnrichmentAnalysis (GSEA) - enrichment plot (5) and Network Topology-based Analysis (NTA)
REF:https://academic.oup.com/nar/article/47/W1/W199/5494758?login=true
[1] "Asthma TFs:" [1] "GATA3" "TCF7" "CEBPA" "SMAD3" "TBX21" "BACH2" "IRF1"
Reduced gene sets with weighted set cover
Pathway and disease enrichment results¶
Three databases combined: "pathway_KEGG","disease_Disgenet", "disease_OMIM"
Reduced gene sets with weighted set cover
Test enrichment for target genes of T subset marker TFs¶
T subset marker TFs were selected based on the top 10 normalized target sizes across cell types.
Biological Process and Molecular function GO terms
Pathways and Diseases GO terms
All other celltype-TF pairs have no significant enrichment except for Treg-E2F4 and Treg-E2F3.