TY - JOUR T1 - Qtlizer: comprehensive QTL annotation of GWAS results JF - bioRxiv DO - 10.1101/495903 SP - 495903 AU - Matthias Munz AU - Inken Wohlers AU - Eric Simon AU - Hauke Busch AU - Arne S. Schaefer AU - Jeanette Erdmann Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/03/13/495903.abstract N2 - Exploration of genetic variant-to-gene relationships by quantitative trait loci (QTLs) helps to identify candidate causal variants and genes in post genome-wide association study analyses. However, the wide range of public QTL databases and the lack of batch annotation features make it cumbersome to investigate these relationships in a comprehensive manner. In this work, we introduce the tool ‘Qtlizer’ to annotate lists of common variants and genes in humans with associated changes in gene expression and protein abundance using the, to-date, most comprehensive database of published QTLs. The features include incorporation of LD variants, sophisticated prioritization functionality and linking to other resources. The web application of Qtlizer is available at http://genehopper.de/qtlizer, a guide on how to use the REST API is available at http://genehopper.de/rest. ER -