Figure 2

Sample network visualization constructed for type 1 diabetes. The risk variants were selected using the greedy RLS on the WTCCC type 1 diabetes GWAS data and the UK National Blood Services’ controls, extended with those genes selected in another work [62]. The biological processes and pathways were then mapped using DAVID [112, 113], and the network visualization was done with the Enrichment Map plugin for Cytoscape [114, 115]. The nodes represent pathways and the edges are the amount of overlap between the members of the pathways. The visualized network represents a selected sub-network of complex interconnections and cross-talks between a number of pathways, including MHC-related processes and other biological pathways associated with diabetes phenotypes. The pathways were identified initially using DAVID, with the criteria that they demonstrate enrichment when compared to the genome-wide background. The retrieved pathways were subsequently filtered in Cytoscape through the Enrichment Map plugin using the false-discovery rate and overlap coefficient to filter out non-significant pathways.