A DiVaMo analysis method to identify relevant metabolic pathways under pathological conditions of Alzheimer and breast cancer

Pathological conditions are associated with altered gene expression and related pathways. We propose a new method, based on hypothesis testing, to compute transcriptome data and underlying pathway alteration, based a new DEG computation criterium, that go further GSEA (Gene Set Enrichment Analisys). The method, called DiVaMo (Discrete Variation Model), given a pathway p, evaluates the aggregated discriminating power S(p) of p, based on a "weighted sum" of how strong is the discriminating power of each gene of p for each condition / control pair of samples.