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QEA is a modified version of the popular Gene Set Enrichment Analysis which utilises the Geoman’s Global Test algorithm and allows different sized sets of metabolites to be compared (Hendrickx et al. 2012). The test avoids problems associated with multiple hypothesis testing, and provides a single p-value with an accompanying FDR for the group, rather than individual significance values for each metabolite. QEA is a novel way to identify biologically meaningful patterns in metabolite concentration changes for quantitative metabolomic studies. The approach has the potential to identify subtle but coordinated changes among a group of related compounds, which may go undetected with conventional statistical

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Network Topology Analysis (NTA) examines the local positioning of significantly altered metabolites within the pathways annotated by KEGG. NTA estimates a Pathway Impact index using a measure of the centrality (Relative Betweeness Centrality) of detected metabolites in relation to all compounds within a given metabolic network. Centrality is a local quantitative measure of the position of a metabolite relative to the other metabolites by calculating the number of shortest paths going through the target compound, which is used to estimate a metabolite’s relative importance or role in network organization. The overall pathway impact is the cumulative value of the importance measures of the detected/matched metabolites normalized by the sum of the importance measures of all the metabolites within a particular pathway. The results of QEA and NTA can be graphically displayed together in a scatterplot; where the y-axis represents pathway enrichment p-values, and the x-axis represents the Pathway Impact scores. In order to assess the effect of Cu exposure duration on the differential regulation of the enriched biochemical pathways, the results of the QEA and NTA analyses for each timeframe were plotted together so that any shifts in the significance of particular metabolic pathways could more easily be