Fig 2. Pathway relevance scoring.

Given a subset of the global similarity matrix (S_exp S_cnv, S_mut, S_met, see Fig 1) and a set of genes (a,b,d) constituting a pathway P, a score for each input dataset is calculated by first removing genes from S_exp S_cnv, S_mut, S_met that do not belong to the pathway and then taking the average of all remaining values in S_exp S_cnv, S_mut, S_met. This process is repeated for n randomly generated gene sets (with the same number of genes as the pathway P) yielding n scores for each input dataset. The random pathway scores are used to calculate a p-value for obtaining the pathway scores purely by chance. The resulting p-values are multiplied, resulting in a single aggregated pathway score.