Functional mapping and annotation of genetic associations with FUMA
By Kyoko Watanabe, E. Taskesen, Arjen van Bochoven, Danielle Posthuma. 2017
3,703 citations recorded by the source corpus.
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. Prioritizing genetic variants is a major challenge in genome-wide association studies. Here, the authors develop FUMA, a web-based bioinformatics tool that uses a combination of positional, eQTL and chromatin interaction mapping to prioritize likely causal variants and genes.
Subfields: Genetics, Molecular Biology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Genetics
- Henrik Walter
- Andreas Meyer-Lindenberg
- Paul M. Thompson
- Anne H. O'Donnell-Luria
- Tian Ge
- Daniel R. Weinberger
- Lars Nyberg
- Ian J. Deary
In Molecular Biology
- Henrik Walter
- Paul M. Thompson
- H. H. Hulshoff Pol
- Andreas Meyer-Lindenberg
- Vince D. Calhoun
- Daniel R. Weinberger
- Ian J. Deary
- Simon E. Fisher
Citations in the corpus
- Transcript expression-aware annotation improves rare variant discovery and interpretation (2019, methodology): “9 for pathway enrichment analysis and used the web browser for FUMA GENE2FUNC feature(40), which incorporates Reactome(41), KEGG(42), Gene Ontology(43) (GO) as well as other ontologies.”
- The genetic architecture of the human cerebral cortex (2020, methodology): “This SNP is in high LD with SNPs associated with educational attainment (28) and is an eQTL forRPS26 in the fetal (34) and adult cortex (30) [t test of Pearson’s”