Dear all,
I’m performing Quantitative Enrichment Analysis (QEA) in MetaboAnalyst. I’m wondering about the utility of normalization, scaling, or data transformation at this specific step. Since QEA uses concentration or intensity values , does applying normalization or scaling (e.g., log transformation, pareto scaling, etc.) improve the biological interpretability or robustness of the enrichment results? I’ve noticed that in the literature, it’s not always clearly specified whether normalization or transformation should be applied before QEA, which adds to the uncertainty. I´d appreciate any insights. Thank you for your help! 
QEA is based on our standard workflow including those steps you mentioned. I don’t see any uncertainty.
Thank you for your reply. What I would like to know is how can I visualize or judge the impact of normalization/scaling on enrichment. For instance, when conducting PLS-DA on normalized data it improves group separation and reduces within-group distance. Is there an equivalent for QEA?
This will include using at least two modules during data analysis. This is a feature of our Pro version, which allows you to compare effects of different parameters based on seperation p-values, number of significant features, classification performance, etc
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