Functional mapping and annotation of genetic associations with FUMA

Kyoko Watanabe, Erdogan Taskesen, Arjen van Bochoven, Danielle Posthuma

Research output: Contribution to JournalArticleAcademicpeer-review


A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.

Original languageEnglish
Article number1826
Pages (from-to)1826
JournalNature Communications
Issue number1
Publication statusPublished - 28 Nov 2017


This work was funded by The Netherlands Organization for Scientific Research (NWO VICI 453-14-005) and Ingrosyl. We thank the GIANT consortium, WTCCC and PGC for providing GWAS summary statistics and GTEx Portal for RNA-seq and eQTL data. We also thank Prof Patrick Sullivan for discussion of 3D chromatin interaction data.

FundersFunder number
Netherlands Organization for Scientific Research
Nederlandse Organisatie voor Wetenschappelijk OnderzoekVICI 453-14-005


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