Fig. 1

Analysis flow in NEArender. The original matrix of 'omics' (mutation, methylation, expression etc.) data described a limited number of samples (patients etc.) with a much larger number of gene feature rows. At the first, preparatory step each sample was described via a characteristic sample-specific altered gene set (AGS). In parallel, a collection of functional gene sets (FGS) that share certain functionally annotations (within each set) was downloaded or prepared otherwise. A global gene/protein network (NET) was also provided (possibly selected from a number of alternatives based on benchmark results). In the course of network enrichment analysis (NEA) each AGS received as many NEA scores as there were FGSs, i.e. obtained coordinates in the multidimensional FGS space. This created an output matrix of the same number of sample columns but many fewer rows