Functional Mapping and Annotation of Genome-Wide Association Studies

FUMA is a platform that can be used to annotate, prioritize, visualize and interpret GWAS results.
The SNP2GENE function takes GWAS summary statistics as an input, and provides extensive functional annotation for all SNPs in genomic areas identified by lead SNPs.
The GENE2FUNC function takes a list of gene IDs (as identified by SNP2GENE or as provided manually) and annotates genes in biological context
To submit your own GWAS, login is required for security reason. If you have't registered yet, you can do from here.
You can browse public results of FUMA (including example jobs) from Browse Public Results without registration or login.

Please post any questions, suggestions and bug reports on Google Forum: FUMA GWAS users.
If you would like to be in the mailing list, please send an email to k.watanabe@vu.nl. Only major updates will be announced through email (low traffic).

When using FUMA, please cite the following.
K. Watanabe, E. Taskesen, A. van Bochoven and D. Posthuma. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 8:1826. (2017).
When using cell type analysis, please cite the following.
K. Watanabe, M. Umicevic Mirkov, C. de Leeuw, M. van den Heuvel and D. Posthuma. Genetic mapping of cell type specificity for complex traits. Nat. Commun. 10:3222. (2019).
Depending on which results you are going to report, please also cite the original study of data sources/tools used in FUMA (references are available at links or tutorial for the cell type specificity analysis for scRNA-seq data).