Node reference

Pathway nodes.

Over-representation analysis on a DEG list: extract the top N marker genes per cluster, then test them against GO / KEGG and other libraries. These nodes rank a gene list; when you need continuous PROGENy, Hallmark or CollecTRI scores computed from the expression matrix, use the Functional Activity nodes instead — the two answer different questions and reports keep them in separate sections.

02 nodesCategory · pathwayin 3 templates

Enrichr sends gene symbols to a remote service

Pathway Enrichment queries the online Enrichr service by default, which means the gene list itself leaves your machine (no expression values, no per-cell data). If that is not acceptable, supply a local gene-set library through the Resource Center and the analysis stays entirely local. Enrichr also rate-limits; the node retries when it is told to slow down.

Top DEG Gene List

extractGeneListsince v0.9.0-beta.25 (renamed from Extract Gene List)

Extract top N DEG genes per cluster as a deduplicated gene list (renamed from "Extract Gene List"). Reads adata.uns[key] from DEG Analysis. Output stored in uns and passed to Pathway Enrichment or Marker Visualization.

Node LibraryscRNA-seq

InAnnData (with DEG results)

OutAnnData (uns gene list)

Parameters (7)

Name	Type	Default	Description
`key`	text	`rank_genes_groups`	adata.uns key for DEG results.
`n_top_genes`	number	`5`	Top genes per cluster (no max).
`group_order`	text	—	Custom cluster order (comma-separated).
`filter_by_pval`	checkbox	`false`	Keep only genes with Benjamini-Hochberg adjusted p-value below pval_threshold. Off = top-ranked genes regardless of significance.
`pval_threshold`	number	`0.05`	Adjusted p-value cutoff used when filter_by_pval is true.
`filter_by_lfc`	checkbox	`false`	Keep only genes up-regulated in the group with log2 fold change >= lfc_threshold.
`lfc_threshold`	number	`0.5`	Minimum log2 fold change used when filter_by_lfc is true.

Pathway Enrichment

pathwayEnrichment

GO/KEGG enrichment per cluster using gseapy + Enrichr REST API. Runs per-cluster on marker genes from DEG Analysis. Stores results in adata.uns["pathway_enrichment"]. Queries the Enrichr web service — the one remote service in the Resource Center, enabled once there before a run.

Node LibraryscRNA-seq

InAnnData (with DEG results)

OutAnnData (uns["pathway_enrichment"])

Parameters (8)

Name	Type	Default	Description
`rank_key`	text	`rank_genes_groups`	adata.uns DEG key.
`gene_sets`	text	`GO_Biological_Process_2023,KEGG_2021_Human`	Comma-separated Enrichr libraries.
`organism`	select	`Human`	"Human" or "Mouse".
`pval_threshold`	number	`0.05`	Marker p-value cutoff.
`lfc_threshold`	number	`1.0`	Marker log-fold-change cutoff.
`min_de_genes`	number	`3`	Min DEGs to run for a cluster.
`ora_background`	select	`tested_genes`	Universe for the over-representation test: 'tested_genes' (the genes DEG Analysis tested — adata.raw when it ranked raw, else var_names; the standard choice) or 'genome' (Enrichr's implicit whole-library background). A universe under 50 genes falls back to 'genome' with a warning. The result reports the background used.
`n_top_terms`	number	`10`	Top terms per cluster per gene set.

Annotation

Functional Activity