PAGEANT: personal access to genome and analysis of natural traits

This is the final version. Available on open access from Oxford University Press via the DOI in this recordData availability: PAGEANT code is available at https://github.com/jielab/pageantGWASs have identified numerous genetic variants associated with a wide variety of diseases, yet despite the wide availability of genetic testing the insights that would enhance the interpretability of these results are not widely available to members of the public. As a proof of concept and demonstration of technological feasibility, we developed PAGEANT (Personal Access to Genome & Analysis of Natural Traits), usable through Graphical User Interface or command line-based version, aiming to serve as a protocol and prototype that guides the overarching design of genetic reporting tools. PAGEANT is structured across five core modules, summarized by five Qs: (i) quality assurance of the genetic data; (ii) qualitative assessment of genetic characteristics; (iii) quantitative assessment of health risk susceptibility based on polygenic risk scores and population reference; (iv) query of third-party variant databases (e.g. ClinVAR and PharmGKB) and (v) quick Response code of genetic variants of interest. Literature review was conducted to compare PAGEANT with academic and industry tools. For 2504 genomes made publicly available through the 1000 Genomes Project, we derived their genomic characteristics for a suite of qualitative and quantitative traits. One exemplary trait is susceptibility to COVID-19, based on the most up-to-date scientific findings reported.National Key Research and Development Program of ChinaPeking University Research Initiation FundINNOVA PACKAGE Inc. (Fujian, China