SNPs in LD of independent significant SNPs will not be prioritized by FUMA. eQTL mapping is used to map SNPs to genes which they show a significant eQTL association with (i.e., the expression of that gene is associated with allelic variation at the SNP). eQTL mapping uses information from 4 data repositories (GTEx8, Blood eQTL browser16, BIOS QTL browser17 and BRAINEAC18), and is currently based on cis-eQTLs which can map SNPs to genes up to 1 Mb apart. Users can select tissue/cell types that are relevant to the phenotype of interest, and eQTLs can be filtered either by nominal P-value or FDR provided by the original data sources (Methods and Supplementary Note 2). Chromatin interaction mapping is used to map SNPs to genes when there is a significant chromatin interaction between the disease-associated regions and nearby or distant genes. Chromatin interaction mapping can involve long-range interactions as it does not have a distance boundary as in eQTL mapping. FUMA currently contains Hi-C data of 14 tissue types and seven cell lines from the study of Schmitt et al.11, yet new chromatin interaction data will be added when it becomes available and FUMA also allows users to upload their own chromatin
