<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>GWAS summary statistics of All of Us</dcterms:title><dcterms:identifier>https://doi.org/10.7910/DVN/FAWEQK</dcterms:identifier><dcterms:creator>Zhang, Haoyu</dcterms:creator><dcterms:publisher>Harvard Dataverse</dcterms:publisher><dcterms:issued>2023-06-13</dcterms:issued><dcterms:modified>2023-09-06T14:56:38Z</dcterms:modified><dcterms:description>This dataset includes GWAS (Genome-Wide Association Studies) summary statistics for two traits across three diverse ancestries. These traits and ancestries form part of the study outlined in the manuscript: "A new method for multiancestry polygenic prediction improves performance across diverse populations". The research manuscript can be accessed via this link: https://www.biorxiv.org/content/10.1101/2022.03.24.485519v5.abstract.

The two traits explored in this dataset include height and body mass index (bmi). These traits were examined across three ancestral backgrounds: African American (AFR), Latino (AMR), and European (EUR).</dcterms:description><dcterms:subject>Medicine, Health and Life Sciences</dcterms:subject><dcterms:subject>Genome-wide association studies</dcterms:subject><dcterms:isReferencedBy>Zhang, Haoyu, et al. "A new method for multiancestry polygenic prediction improves performance across diverse populations" Nature Genetics (in Press).</dcterms:isReferencedBy><dcterms:date>2023-06-13</dcterms:date><dcterms:contributor>Zhang, Haoyu</dcterms:contributor><dcterms:dateSubmitted>2023-06-13</dcterms:dateSubmitted><dcterms:license>CC0 1.0</dcterms:license></metadata>