Review iCPAGdb: Explore pre-calculated iCPAGdb results
Upload GWAS and compute: Upload your own GWAS summary statistics (SNPs and p-values for a desired phenotype) then have iCPAGdb clump the data and run analyses against datasets in iCPAGdb
iCPAGdb (interactive Cross-Phenotype Analysis of GWAS database) provides an atlas of human traits connected through shared genetic architecture. While genome-wide association studies (GWAS) have successfully identified thousands of genetic variants associated with human diseases and traits, understanding how genetic differences impact disease risk and severity remains a formidable challenge. iCPAGdb integrates the results of GWAS across phenotypic scales, identifying and quantifying the significance of pleiotropic loci that impact molecular, cellular, and organismal traits. The goal is to provide a resource that allows experts on a particular human trait to easily develop hypotheses for molecular and cellular phenotypes that underlie the physiology of that trait. Molecules and cellular pathways implicated in this way could serve as novel biomarkers or targets for therapeutic approaches.iCPAGdb leverages:
Users can explore pre-computed iCPAGdb output for these datasets or upload their own GWAS results for rapid comparison against these datasets. As an example, we demonstrate the utility of iCPAGdb with a published GWAS of severe COVID-19: Ellinghaus D, Degenhardt F, Bujanda L, Buti M, Albillos A, Invernizzi P, et al. Genomewide Association Study of Severe Covid-19 with Respiratory Failure. N Engl J Med. 2020.
Info on the web app: iCPAGdb web app design