We have built an integrated system for incorporating GWAS, eQTL, pQTL and epigenetics data resources together and provide statistical genetics analysis of this data within an easy-to-navigate portal, which requires compatibility of data features (for example genes are mapped to Ensembl gene IDs and variants to chromosomal position on genome build GRCh38). To integrate genetic and functional genomics data from the wide array of disease association studies and functional genomics datasets, a major challenge is the mapping of traits from different data resources to a standardised terminology to allow systematic aggregation of associations linked to the same underlying trait or disease. We have used the Experimental Factor Ontology (EFO) to map disease terms across data resources and have added new EFO terms where required. This involves extensive manual review for each new data resource added to ensure automatic mappings are correct. Another challenge is the availability and format of data, and the requirement of making human genetic and disease data publicly available within an ethical framework. This limits the resources and types of data we are able to bring into
