{"id":705,"date":"2023-11-13T13:00:12","date_gmt":"2023-11-13T13:00:12","guid":{"rendered":"https:\/\/terrabioappdev.wpenginepowered.com\/neale-lab-uk-biobank-on-terra\/"},"modified":"2023-12-27T04:56:02","modified_gmt":"2023-12-27T04:56:02","slug":"neale-lab-uk-biobank-on-terra","status":"publish","type":"post","link":"https:\/\/terra.bio\/neale-lab-uk-biobank-on-terra\/","title":{"rendered":"Managing Access to UK Biobank Data on Terra"},"content":{"rendered":"<h1><\/h1>\n<p><span style=\"font-weight: 400;\">Having access to good data is crucial for genomics research. Without large-scale datasets, there\u2019s little chance of uncovering the genetic underpinnings of disease. This is particularly important when studying diseases whose risk is determined by a large number of genes, each of which has a relatively small effect.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">But analyzing and managing these large datasets can be challenging. This is particularly true when the data are protected, so that only approved researchers can access it. Because of these challenges, many good scientific stories happen alongside equally-interesting stories about data management.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In one such story, Terra\u2019s data management tools allowed researchers to access data from the <\/span><a href=\"https:\/\/www.ukbiobank.ac.uk\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">UK Biobank<\/span><\/a><span style=\"font-weight: 400;\">. In turn, this access has fueled many innovative projects that were only possible with large-scale data.\u00a0\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Getting the data onto the Cloud<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">The UK Biobank amasses genotypic and phenotypic data from roughly half a million participants in the United Kingdom. Research groups interested in working with the data can apply for access to this data set. In 2017, a group of Broadies across different research interests \u2014 including Krishna Aragam, Andrea Ganna, and Mary Hross \u2014 understood that having a single dataset available on the Cloud (and on the Broad Cluster) would allow more researchers to study the keys to disease, and simultaneously reduce storage costs. As a result, Ben Neale\u2019s lab sponsored a project to undertake this work. The project\u2019s storage is funded by Broad ITS and managed by Sam Bryant, who was a Senior Data Management Specialist at the time. Bryant has since become the Associate Director of Data Management at the Broad\u2019s Stanley Center for Psychiatric Research.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Working with such large data was no easy task. To start, it took a long time to obtain the files \u2014 at the time, the UK Biobank limited downloads to 10 concurrent files. So, Sam Bryant got approval to access genotype and phenotype data from roughly half a million participants, then spent about two weeks downloading it onto the Broad\u2019s on-premises cluster. From there, he uploaded the data to a Terra workspace in the Cloud.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Managing access to the data<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">With these data in hand, Bryant faced a second challenge: managing who could use the data. The UK Biobank uses a careful approval process to protect their data. So now Bryant needed a way to ensure that only approved users could access the Terra dataset.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The solution was to create a Terra Group of approved researchers. Researchers who wanted to access the data \u2014 including the Neale lab\u2019s collaborators \u2014 applied for approval from the UK Biobank, which then let Bryant know who he could add to the Terra group. Once added to the group, collaborators could access the data \u2014 from inside or outside of Terra \u2014 in order to analyze it.\u00a0<\/span><\/p>\n<h4><span style=\"font-weight: 400;\">An alternative method: using DUOS to manage controlled data on Terra<\/span><\/h4>\n<p><span style=\"font-weight: 400;\">In many cases, Bryant\u2019s method is still the best way to share controlled-access data with collaborators. However, it works best when data managers are sharing their data with known collaborators. DUOS offers an alternative to share controlled-access data from the Broad and the National Human Genome Research Institute (NHGRI). DUOS speeds the data-access application process by automatically updating access permissions whenever someone is approved. This system makes it easy to share data with unknown researchers, as well as collaborators. You can learn more about how DUOS makes it easier to access controlled-access data in <\/span><a href=\"https:\/\/terra.bio\/streamlining-data-access-duos-introduces-automatic-access-permission-updates\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Streamlining Data Access<\/span><\/a><span style=\"font-weight: 400;\"> and on <\/span><a href=\"https:\/\/broad-duos.zendesk.com\/hc\/en-us\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">DUOS\u2019 documentation<\/span><\/a><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">The data\u2019s scientific impact<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Since 2017, research groups have accessed the UK Biobank dataset on Terra to answer questions about several aspects of human health. These include coronary artery disease (<\/span><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/35294538\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Fahed et al., 2022<\/span><\/a><span style=\"font-weight: 400;\">; <\/span><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/35544052\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Patel et al., 2022<\/span><\/a><span style=\"font-weight: 400;\">; <\/span><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/37414900\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Patel et al., 2023<\/span><\/a><span style=\"font-weight: 400;\">; <\/span><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/36723951\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Dron et al., 2023<\/span><\/a><span style=\"font-weight: 400;\">; <\/span><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/36215124\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Khera et al., 2022<\/span><\/a><span style=\"font-weight: 400;\">); Alzheimer\u2019s (<\/span><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/36048760\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Paranjpe et al., 2022<\/span><\/a><span style=\"font-weight: 400;\">); obesity (<\/span><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/35773277\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Agrawal et al., 2022<\/span><\/a><span style=\"font-weight: 400;\">); liver disease (<\/span><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/34957434\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Haas et al., 2021<\/span><\/a><span style=\"font-weight: 400;\">); heteroplasmy (<\/span><a href=\"https:\/\/www.nature.com\/articles\/s41586-023-06426-5)\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Gupta et al., 2023<\/span><\/a><span style=\"font-weight: 400;\">); and clonal hematopoiesis (<\/span><a href=\"https:\/\/www.nature.com\/articles\/s41467-023-41315-5\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Brown et al., 2023<\/span><\/a><span style=\"font-weight: 400;\">). These data have also supported a growing understanding of how the human genome and phenome are structured \u2013 for example, uncovering correlations within the human phenome (<\/span><a href=\"https:\/\/www.medrxiv.org\/content\/10.1101\/2022.09.02.22279546v1\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Carey et al., 2022<\/span><\/a><span style=\"font-weight: 400;\">). In addition, the UK Biobank dataset has helped researchers better understand the effects of a dataset\u2019s size and diversity on machine learning models (<\/span><a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2022.10.21.513123v2\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Cui et al., 2023<\/span><\/a><span style=\"font-weight: 400;\">; <\/span><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S2666247723000167?via%3Dihub\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Majara et al., 2023<\/span><\/a><span style=\"font-weight: 400;\">).<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">How can you access this data?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">The Broad\u2019s UK Biobank dataset is still available on Terra. This dataset is a subset of the full UK Biobank data \u2014 the remainder is accessible via DNANexus.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you\u2019d like to leverage this dataset for your own research, and you\u2019ve already applied for access to the UK Biobank, follow the <\/span><a href=\"https:\/\/docs.google.com\/document\/d\/15k0kPhkiemjBA8TqX00UK2Rf2IKFpD8-yUx4DetZ-RI\/edit\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">instructions in this document<\/span><\/a><span style=\"font-weight: 400;\">. If you have not yet applied for access to the UK Biobank, contact Sam Bryant directly at <\/span><a href=\"mailto:sbryant@broadinstitute.org\"><span style=\"font-weight: 400;\">sbryant@broadinstitute.org<\/span><\/a><span style=\"font-weight: 400;\">. And to learn more about sharing controlled data on Terra, see <\/span><a href=\"https:\/\/support.terra.bio\/hc\/en-us\/articles\/360042670651-Best-practices-for-sharing-and-protecting-data-resources\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Best practices for sharing and protecting data resources<\/span><\/a><span style=\"font-weight: 400;\"> and <\/span><a href=\"https:\/\/support.terra.bio\/hc\/en-us\/articles\/360024617851-Managing-access-to-shared-data-and-tools-with-groups\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Managing access to shared data and tools with groups<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><i><span style=\"font-weight: 400;\">Many thanks to Sam Bryant, Caroline Cusick, and Jonathan Lawson for their help preparing this post.<\/span><\/i><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Having access to good data is crucial for genomics research. Without large-scale datasets, there\u2019s little chance of uncovering the genetic underpinnings of disease. This is particularly important when studying diseases whose risk is determined by a large number of genes, each of which has a relatively small effect.\u00a0 But analyzing and managing these large datasets [&hellip;]<\/p>\n","protected":false},"author":58,"featured_media":706,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[119],"tags":[197,196,207],"class_list":["post-705","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-most-recent","tag-controlled-access","tag-terra","tag-uk-biobank"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Managing Access to UK Biobank Data on Terra - Terra<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/terra.bio\/neale-lab-uk-biobank-on-terra\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Managing Access to UK Biobank Data on Terra - Terra\" \/>\n<meta property=\"og:description\" content=\"Having access to good data is crucial for genomics research. Without large-scale datasets, there\u2019s little chance of uncovering the genetic underpinnings of disease. 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