PhenoScanner is a curated database of publicly available results from large-scale genetic association studies, designed to facilitate 'phenome scans' by cross-referencing genetic variants with many phenotypes. It contains over 350 million association results and over 10 million unique genetic variants, mostly single nucleotide polymorphisms. The database is accompanied by a web-based tool that allows users to query associations with specified variants, providing results according to the same effect and non-effect alleles for each input variant. The tool also enables searching for trait associations with proxies of the input variants, calculated using European samples from 1000 Genomes and Hapmap. PhenoScanner is available at www.phenoscanner.medschl.cam.ac.uk. It addresses the challenge of efficiently cross-referencing genetic variants with a wide range of phenotypes, which is crucial for understanding disease pathways and biology. Existing GWAS result catalogues, such as the NHGRI-EBI GWAS catalog and dbGaP, often focus on variants robustly associated with specific traits and lack systematic search capabilities. PhenoScanner aligns genotype-phenotype associations across traits and proxies, providing users with an easily interpretable formatted output file. It includes all available results, unlike current catalogues that filter based on association strength. The tool allows users to enter one variant or upload up to 50 variants, and it identifies proxies of the specified variants based on a user-specified pairwise r² threshold. Association results are collated and presented with respect to the same effect and non-effect alleles for each variant. The output is a file of associations, which can be downloaded. There is also a P value filter to retain results with study-specific P values below a selected threshold. PhenoScanner has been shown to be effective in identifying associations, even when direct associations for a variant are unavailable, by using proxies. For example, rs10840293 was used with proxies from 1000 Genomes and an r² cut-off of 0.8, resulting in over 1000 associations within 10 seconds. This tool is expected to make cross-referencing genetic variants with many phenotypes faster and more efficient. Funding for this work came from various sources, including the UK Medical Research Council, Pfizer, British Heart Foundation, and the European Research Council. No conflicts of interest were declared.PhenoScanner is a curated database of publicly available results from large-scale genetic association studies, designed to facilitate 'phenome scans' by cross-referencing genetic variants with many phenotypes. It contains over 350 million association results and over 10 million unique genetic variants, mostly single nucleotide polymorphisms. The database is accompanied by a web-based tool that allows users to query associations with specified variants, providing results according to the same effect and non-effect alleles for each input variant. The tool also enables searching for trait associations with proxies of the input variants, calculated using European samples from 1000 Genomes and Hapmap. PhenoScanner is available at www.phenoscanner.medschl.cam.ac.uk. It addresses the challenge of efficiently cross-referencing genetic variants with a wide range of phenotypes, which is crucial for understanding disease pathways and biology. Existing GWAS result catalogues, such as the NHGRI-EBI GWAS catalog and dbGaP, often focus on variants robustly associated with specific traits and lack systematic search capabilities. PhenoScanner aligns genotype-phenotype associations across traits and proxies, providing users with an easily interpretable formatted output file. It includes all available results, unlike current catalogues that filter based on association strength. The tool allows users to enter one variant or upload up to 50 variants, and it identifies proxies of the specified variants based on a user-specified pairwise r² threshold. Association results are collated and presented with respect to the same effect and non-effect alleles for each variant. The output is a file of associations, which can be downloaded. There is also a P value filter to retain results with study-specific P values below a selected threshold. PhenoScanner has been shown to be effective in identifying associations, even when direct associations for a variant are unavailable, by using proxies. For example, rs10840293 was used with proxies from 1000 Genomes and an r² cut-off of 0.8, resulting in over 1000 associations within 10 seconds. This tool is expected to make cross-referencing genetic variants with many phenotypes faster and more efficient. Funding for this work came from various sources, including the UK Medical Research Council, Pfizer, British Heart Foundation, and the European Research Council. No conflicts of interest were declared.