Gene set enrichment analysis is a method to identify classes of genes or proteins that are over-represented in a large set of genes or proteins, and may have an association with disease phenotypes. The method uses statistical approaches to identify significantly enriched or depleted groups of genes. To analyze differential gene expression enrichment of pathways or other gene sets, you may follow the detailed step wise instructions as mentioned in the Transcriptomics course on the OmicsLogic Learn portal: https://learn.omicslogic.com/Learn/course-5-transcriptomics/lesson/09-t2-differential-gene-expression-and-gene-enrichment-analysis

Instructions to set HumanGAGE parameters: 

1. Col Header :  Choose Yes if there header present in the data.
2. Column with Gene ID: Here, you need to provide a column Number having Gene Symbol.
3. Column with Differential Expression Measure: Here, you need to provide a column Number having LogFC or fold change value.
4. Statistics Type: Choose Non-parametric if you provide input file from the DESeq2 or EdgeR or Wilcoxon Test results.
5. Gene Set: KEGG pathway if you want to get pathway, or you can choose GO terms if you want that.
6. Expression Change Direction: Choose Both direction

FDR threshold: Need to provide FDR value = 0.05 if you want only significant pathways. At this step, maybe you can choose much higher 1 or 2, so you will obtain all pathways and then you can select significant pathway from the table.