What are the main differences between mummichog and GSEA in MetaboAnalyst?

The mummichog algorithm implements an over-representation analysis (ORA) method to evaluate pathway-level enrichment based on significant peaks. Users need to specify a pre-defined cutoff based on either t-statistics or fold changes. We note that using top 10% peaks (default in MetaboAnalyst) generally works very well.

An alternative approach is the Gene Set Enrichment Analysis (GSEA) method, which is widely used to test for enriched functions from ranked gene lists. Unlike ORA, GSEA considers the overall ranks of features without using a significance cutoff, and is claimed to be able to detect subtle and consistent changes which could be missed from using ORA-based methods.