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expression-to-pathways

separate

Orchestrates the full path from differential expression results to redundancy-collapsed functional enrichment: choose ORA vs GSEA, convert gene IDs per method, run enrichGO/enrichKEGG/enrichPathway/enrichWP or gseGO/gseKEGG (clusterProfiler, ReactomePA, rWikiPathways), and visualize. Use when a DESeq2/edgeR/limma result must become enriched GO terms, KEGG/Reactome/WikiPathways pathways, or a GSEA leading edge; when the input is a full ranking for all genes (GSEA, named decreasing vector) or only a pre-selected list (ORA plus a defensible background universe); or when assembling DE-to-pathway end to end. The DE list and ranking statistic come from differential-expression/de-results; per-method nuance lives in the pathway-analysis skills.

When to use

• differential expression to functional enrichment
• ORA vs GSEA decision
• gene ID conversion per method
• enrichGO/enrichKEGG/enrichPathway/enrichWP execution
• gseGO/gseKEGG execution
• redundancy-collapsed visualization
• DE-to-pathway end-to-end assembly

When not to use

• re-teaching individual pathway analysis methods
• deriving null/universe/reproducibility theory
• master method-selection tree derivation
• ORA mechanics
• GSEA mechanics
• per-database IDs and live-DB behavior
• generating DE list and ranking statistic
• plotting details

Skill page

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