TopExpressingGenes Process Configuration
Purpose
Identifies and visualizes the top expressing genes per cluster in T/B cells, followed by pathway enrichment analysis. Provides quick cluster characterization by highlighting the most highly expressed genes and their biological functions.
When to Use
- •After:
SeuratClusteringandTOrBCellSelectionprocesses - •Use cases: Quick cluster characterization, identifying dominant gene programs, pathway enrichment
- •Optional process: Enable only when cluster-level expression profiling is needed
Configuration Structure
Process Enablement
toml
[TopExpressingGenes] cache = true
Input Specification
toml
[TopExpressingGenes.in] srtobj = ["SeuratClustering"]
Note: srtobj accepts the output from SeuratClustering or SeuratSubClustering.
Environment Variables
Core Parameters
toml
[TopExpressingGenes.envs] # Number of top expressing genes to identify per cluster n = 250 # Enrichment style enrich_style = "enrichr" # Options: "enrichr", "clusterprofiler" # Enrichment databases dbs = ["KEGG_2021_Human", "MSigDB_Hallmark_2020"]
Enrichment Plot Settings
toml
[TopExpressingGenes.envs.enrich_plots_defaults]
# Plot type: "bar", "dot", "lollipop", "network", "enrichmap", "wordcloud"
plot_type = "bar"
devpars = {res = 100, width = 800, height = 600}
top_term = 10 # Top enriched pathways to show
ncol = 1
Configuration Examples
Minimal Configuration
toml
[TopExpressingGenes] [TopExpressingGenes.in] srtobj = ["SeuratClustering"]
Top 10 Genes with Custom Databases
toml
[TopExpressingGenes] [TopExpressingGenes.in] srtobj = ["SeuratClustering"] [TopExpressingGenes.envs] n = 10 dbs = ["GO_Biological_Process_2025", "Reactome_Pathways_2024"]
Network Visualization
toml
[TopExpressingGenes.envs.enrich_plots."Network"] plot_type = "network" top_term = 15 [TopExpressingGenes.envs.enrich_plots."Enrichmap"] plot_type = "enrichmap"
Common Patterns
Pattern 1: Quick Cluster Overview
toml
[TopExpressingGenes] [TopExpressingGenes.in] srtobj = ["SeuratClustering"] [TopExpressingGenes.envs] n = 10 dbs = ["MSigDB_Hallmark_2020"]
Pattern 2: Detailed Profile
toml
[TopExpressingGenes.envs]
n = 250
enrich_style = "clusterprofiler"
[TopExpressingGenes.envs.enrich_plots]
"KEGG" = {plot_type = "bar", dbs = ["KEGG_2021_Human"]}
"Reactome" = {plot_type = "network"}
Pattern 3: Multiple Visualizations
toml
[TopExpressingGenes.envs] n = 50 [TopExpressingGenes.envs.enrich_plots."Bar"] plot_type = "bar" [TopExpressingGenes.envs.enrich_plots."Word Cloud"] plot_type = "wordcloud"
Difference from ClusterMarkers
| Aspect | TopExpressingGenes | ClusterMarkers |
|---|---|---|
| Finds | Highest expressed genes within clusters | Genes differentially expressed between clusters |
| Meaning | Basal/dominant expression | Distinguishing markers |
| Stat test | None (average expression) | Statistical (Wilcoxon, MAST) |
| Use case | Cluster identity/function | Marker discovery |
| Output | Top N genes | DEGs with p-values/FC |
Recommendation: Use both processes:
- •
TopExpressingGenes: Quick overview of dominant programs - •
ClusterMarkers: Rigorous marker identification
Dependencies
- •Upstream:
SeuratClustering,TOrBCellSelection(for TCR route) - •Downstream: None (terminal analysis process)
Validation Rules
- •
n: Positive integer (typically 10-500) - •
dbs: Valid enrichit/Enrichr database names or local GMT paths - •
enrich_style: "enrichr" or "clusterprofiler" - •
plot_type: Valid scplotter plot type
Troubleshooting
Ribosomal/Mitochondrial Gene Dominance
Issue: Housekeeping genes (RPS, RPL, MT-) dominate
Solutions: Increase n, use ClusterMarkers, filter genes in SeuratPreparing
Empty Enrichment Results
Issue: No pathways enriched
Solutions: Increase n to 100-500, verify species (UPPERCASE=human, TitleCase=mouse)
Plot Rendering Errors
Issue: Plots fail to render
Solutions: Reduce top_term (5-15), use simpler plots (bar, dot)
Performance Issues
Issue: Process too slow
Solutions: Reduce n, use fewer databases, disable enrichment: dbs = []
External References
Databases (enrichit)
- •
KEGG_2021_Human- KEGG pathways - •
MSigDB_Hallmark_2020- Hallmark gene sets - •
GO_Biological_Process_2025- GO Biological Process - •
Reactome_Pathways_2024- Reactome pathways - •See: https://pwwang.github.io/enrichit/reference/FetchGMT.html
Plot Types (scplotter)
- •
bar- Bar chart - •
dot- Dot plot - •
lollipop- Lollipop plot - •
network- Network visualization - •
enrichmap- Enrichment map - •
wordcloud- Word cloud
Enrichment Styles
- •
enrichr- Fisher's exact test - •
clusterprofiler- Hypergeometric test
See Also
- •
TopExpressingGenesOfAllCells- Top genes before T/B selection - •
ClusterMarkers- Differential expression analysis