Unknown

Dataset Information

0

Functional mapping and annotation of genetic associations with FUMA.


ABSTRACT: 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.

SUBMITTER: Watanabe K 

PROVIDER: S-EPMC5705698 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications

Functional mapping and annotation of genetic associations with FUMA.

Watanabe Kyoko K   Taskesen Erdogan E   van Bochoven Arjen A   Posthuma Danielle D  

Nature communications 20171128 1


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  ...[more]

Similar Datasets

| S-EPMC7376057 | biostudies-literature
| S-EPMC8682766 | biostudies-literature
| S-EPMC7749173 | biostudies-literature
2024-10-18 | PXD048272 | Pride
| S-EPMC4573268 | biostudies-literature
| S-EPMC4408026 | biostudies-literature
| S-EPMC8724965 | biostudies-literature
| S-EPMC6117358 | biostudies-literature
| S-EPMC3598525 | biostudies-other
2023-12-31 | GSE233683 | GEO