1
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Skantharajah N, Baichoo S, Boughtwood TF, Casas-Silva E, Chandrasekharan S, Dave SM, Fakhro KA, Falcon de Vargas AB, Gayle SS, Gupta VK, Hendricks-Sturrup R, Hobb AE, Li S, Llamas B, Lopez-Correa C, Machirori M, Melendez-Zajgla J, Millner MA, Page AJ, Paglione LD, Raven-Adams MC, Smith L, Thomas EM, Kumuthini J, Corpas M. Equity, diversity, and inclusion at the Global Alliance for Genomics and Health. Cell Genom 2023; 3:100386. [PMID: 37868041 PMCID: PMC10589617 DOI: 10.1016/j.xgen.2023.100386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/24/2023]
Abstract
A lack of diversity in genomics for health continues to hinder equitable leadership and access to precision medicine approaches for underrepresented populations. To avoid perpetuating biases within the genomics workforce and genomic data collection practices, equity, diversity, and inclusion (EDI) must be addressed. This paper documents the journey taken by the Global Alliance for Genomics and Health (a genomics-based standard-setting and policy-framing organization) to create a more equitable, diverse, and inclusive environment for its standards and members. Initial steps include the creation of two groups: the Equity, Diversity, and Inclusion Advisory Group and the Regulatory and Ethics Diversity Group. Following a framework that we call "Reflected in our Teams, Reflected in our Standards," both groups address EDI at different stages in their policy development process.
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Affiliation(s)
- Neerjah Skantharajah
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Global Alliance for Genomics and Health, Toronto, ON, Canada
| | | | - Tiffany F. Boughtwood
- Australian Genomics, Parkville, VIC, Australia
- Murdoch Children’s Research Institute, Parkville, VIC, Australia
| | | | | | - Sanjay M. Dave
- Department of Biotechnology, Hemchandracharya North Gujarat University, Patan, Gujarat, India
| | - Khalid A. Fakhro
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
- Department of Genetic Medicine, Weill Cornell Medical College, Doha, Qatar
| | - Aida B. Falcon de Vargas
- Hospital Vargas de Caracas, Vargas Medical School, Universidad Central de Venezuela, Caracas, Venezuela
- Hospital de Clínicas Caracas, Caracas, Venezuela
| | | | - Vivek K. Gupta
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia
| | | | | | - Stephanie Li
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Broad Institute, Cambridge, MA, USA
| | - Bastien Llamas
- Australian Centre for Ancient DNA, School of Biological Sciences and The Environment Institute, University of Adelaide, Adelaide, SA, Australia
- ARC Centre of Excellence for Australian Biodiversity and Heritage, University of Adelaide, Adelaide, SA, Australia
- National Centre for Indigenous Genomics, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
- Indigenous Genomics, Telethon Kids Institute, Adelaide, SA, Australia
| | | | - Mavis Machirori
- Ada Lovelace Institute, London, UK
- PEALS, Newcastle University, Newcastle Upon Tyne, UK
| | | | - Mareike A. Millner
- Maastricht University, Health Law and Governance Group, Maastricht, the Netherlands
| | - Angela J.H. Page
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Broad Institute, Cambridge, MA, USA
| | - Laura D. Paglione
- Spherical Cow Group, New York, NY, USA
- Laura Paglione LLC, New York, NY, USA
| | - Maili C. Raven-Adams
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Wellcome Sanger Institute, Hinxton, UK
| | - Lindsay Smith
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Global Alliance for Genomics and Health, Toronto, ON, Canada
| | - Ericka M. Thomas
- The All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Judit Kumuthini
- South African National Bioinformatics Institute, University of Western Cape, Cape Town, South Africa
| | - Manuel Corpas
- School of Life Sciences, University of Westminster, London, UK
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2
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Rambla J, Baudis M, Ariosa R, Beck T, Fromont LA, Navarro A, Paloots R, Rueda M, Saunders G, Singh B, Spalding JD, Törnroos J, Vasallo C, Veal CD, Brookes AJ. Beacon v2 and Beacon networks: A "lingua franca" for federated data discovery in biomedical genomics, and beyond. Hum Mutat 2022; 43:791-799. [PMID: 35297548 PMCID: PMC9322265 DOI: 10.1002/humu.24369] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 03/07/2022] [Accepted: 03/12/2022] [Indexed: 11/05/2022]
Abstract
Beacon is a basic data discovery protocol issued by the Global Alliance for Genomics and Health (GA4GH). The main goal addressed by version 1 of the Beacon protocol was to test the feasibility of broadly sharing human genomic data, through providing simple "yes" or "no" responses to queries about the presence of a given variant in datasets hosted by Beacon providers. The popularity of this concept has fostered the design of a version 2, that better serves real-world requirements and addresses the needs of clinical genomics research and healthcare, as assessed by several contributing projects and organizations. Particularly, rare disease genetics and cancer research will benefit from new case level and genomic variant level requests and the enabling of richer phenotype and clinical queries as well as support for fuzzy searches. Beacon is designed as a "lingua franca" to bridge data collections hosted in software solutions with different and rich interfaces. Beacon version 2 works alongside popular standards like Phenopackets, OMOP, or FHIR, allowing implementing consortia to return matches in beacon responses and provide a handover to their preferred data exchange format. The protocol is being explored by other research domains and is being tested in several international projects.
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Affiliation(s)
- Jordi Rambla
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and TechnologyBarcelonaSpain
- Department of Experimental and Health SciencesUniversitat Pompeu Fabra (UPF), PRBBBarcelonaSpain
| | - Michael Baudis
- Department of Molecular Life SciencesUniversity of Zurich and Swiss Institute of BioinformaticsZurichSwitzerland
| | - Roberto Ariosa
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Tim Beck
- Department of Genetics & Genome BiologyUniversity of LeicesterLeicesterUK
| | - Lauren A. Fromont
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Arcadi Navarro
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and TechnologyBarcelonaSpain
- Department of Experimental and Health Sciences, IBE, Institute of Evolutionary Biology (UPF‐CSIC)Universitat Pompeu Fabra. PRBBBarcelonaSpain
- Institució Catalana de Recerca i Estudis Avançats (ICREA)Universitat Pompeu FabraBarcelonaSpain
- Barcelona Beta Brain Research Center, Pasqual Maragall FoundationBarcelonaSpain
| | - Rahel Paloots
- Department of Molecular Life SciencesUniversity of Zurich and Swiss Institute of BioinformaticsZurichSwitzerland
| | - Manuel Rueda
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Gary Saunders
- European Infrastructure for Translational Medicine, EATRISAmsterdamThe Netherlands
| | - Babita Singh
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | | | - Juha Törnroos
- ELIXIR Finland; CSC ‐ IT Center for Science LtdEspooFinland
| | - Claudia Vasallo
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and TechnologyBarcelonaSpain
| | - Colin D. Veal
- Department of Genetics & Genome BiologyUniversity of LeicesterLeicesterUK
| | - Anthony J. Brookes
- Department of Genetics & Genome BiologyUniversity of LeicesterLeicesterUK
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3
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Boycott KM, Azzariti DR, Hamosh A, Rehm HL. Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking. Hum Mutat 2022; 43:659-667. [PMID: 35537081 PMCID: PMC9133175 DOI: 10.1002/humu.24373] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 03/22/2022] [Indexed: 11/09/2022]
Abstract
The Matchmaker Exchange (MME) was launched in 2015 to provide a robust mechanism to discover novel disease-gene relationships. It operates as a federated network connecting databases holding relevant data using a common application programming interface, where two or more users are looking for a match for the same gene (two-sided matchmaking). Seven years from its launch, it is clear that the MME is making outstanding contributions to understanding the morbid anatomy of the genome. The number of unique genes present across the MME has steadily increased over time; there are currently >13,520 unique genes (~68% of all protein-coding genes) connected across the MME's eight genomic matchmaking nodes, GeneMatcher, DECIPHER, PhenomeCentral, MyGene2, seqr, Initiative on Rare and Undiagnosed Disease, PatientMatcher, and the RD-Connect Genome-Phenome Analysis Platform. The collective data set accessible across the MME currently includes more than 120,000 cases from over 12,000 contributors in 98 countries. The discovery of potential new disease-gene relationships is happening daily and international collaborative teams are moving these advances forward to publication, now numbering well over 500. Expansion of data sharing into routine clinical practice by clinicians, genetic counselors, and clinical laboratories has ensured access to discovery for even more individuals with undiagnosed rare genetic diseases. Tens of thousands of patients and their family members have been directly or indirectly impacted by the discoveries facilitated by two-sided genomic matchmaking. MME supports further connections to the literature (PubCaseFinder) and to human and model organism resources (Monarch Initiative) and scientists (ModelMatcher). Efforts are now underway to explore additional approaches to matchmaking at the gene or variant level where there is only one querier (one-sided matchmaking). Genomic matchmaking has proven its utility over the past 7 years and will continue to facilitate discoveries in the years to come.
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Affiliation(s)
- Kym M. Boycott
- Children’s Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada
| | - Danielle R. Azzariti
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Ada Hamosh
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Heidi L. Rehm
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
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4
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Cabili MN, Lawson J, Saltzman A, Rushton G, O’Rourke P, Wilbanks J, Rodriguez LL, Nyronen T, Courtot M, Donnelly S, Philippakis AA. Empirical validation of an automated approach to data use oversight. Cell Genom 2021; 1:100031. [PMID: 36778584 PMCID: PMC9903839 DOI: 10.1016/j.xgen.2021.100031] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 06/30/2021] [Accepted: 08/07/2021] [Indexed: 10/19/2022]
Abstract
The current paradigm for data use oversight of biomedical datasets is onerous, extending the timescale and resources needed to obtain access for secondary analyses, thus hindering scientific discovery. For a researcher to utilize a controlled-access dataset, a data access committee must review her research plans to determine whether they are consistent with the data use limitations (DULs) specified by the informed consent form. The newly created GA4GH data use ontology (DUO) holds the potential to streamline this process by making data use oversight computable. Here, we describe an open-source software platform, the Data Use Oversight System (DUOS), that connects with DUO terminology to enable automated data use oversight. We analyze dbGaP data acquired since 2006, finding an exponential increase in data access requests, which will not be sustainable with current manual oversight review. We perform an empirical evaluation of DUOS and DUO on selected datasets from the Broad Institute's data repository. We were able to structure 118/123 of the evaluated DULs (96%) and 52/52 (100%) of research proposals using DUO terminology, and we find that DUOS' automated data access adjudication in all cases agreed with the DAC manual review. This first empirical evaluation of the feasibility of automated data use oversight demonstrates comparable accuracy to human-based data access oversight in real-world data governance.
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Affiliation(s)
- Moran N. Cabili
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jonathan Lawson
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Andrea Saltzman
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Greg Rushton
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | | | | | - Tommi Nyronen
- ELIXIR Finland, CSC - IT Center for Science, Espoo, Finland
| | - Mélanie Courtot
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Stacey Donnelly
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA,Corresponding author
| | - Anthony A. Philippakis
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA,Corresponding author
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5
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Lawson J, Cabili MN, Kerry G, Boughtwood T, Thorogood A, Alper P, Bowers SR, Boyles RR, Brookes AJ, Brush M, Burdett T, Clissold H, Donnelly S, Dyke SO, Freeberg MA, Haendel MA, Hata C, Holub P, Jeanson F, Jene A, Kawashima M, Kawashima S, Konopko M, Kyomugisha I, Li H, Linden M, Rodriguez LL, Morita M, Mulder N, Muller J, Nagaie S, Nasir J, Ogishima S, Ota Wang V, Paglione LD, Pandya RN, Parkinson H, Philippakis AA, Prasser F, Rambla J, Reinold K, Rushton GA, Saltzman A, Saunders G, Sofia HJ, Spalding JD, Swertz MA, Tulchinsky I, van Enckevort EJ, Varma S, Voisin C, Yamamoto N, Yamasaki C, Zass L, Guidry Auvil JM, Nyrönen TH, Courtot M. The Data Use Ontology to streamline responsible access to human biomedical datasets. Cell Genom 2021; 1:None. [PMID: 34820659 PMCID: PMC8591903 DOI: 10.1016/j.xgen.2021.100028] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 07/02/2021] [Accepted: 08/09/2021] [Indexed: 11/25/2022]
Abstract
Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset's allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers' discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide.
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Affiliation(s)
- Jonathan Lawson
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Moran N. Cabili
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Giselle Kerry
- European Molecular Biology Laboratory—European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Tiffany Boughtwood
- Australian Genomics, Murdoch Children’s Research Institute, Parkville, VIC, Australia
| | - Adrian Thorogood
- Centre of Genomics and Policy, Department of Human Genetics, McGill University, Montreal, QC, Canada,ELIXIR-Luxembourg, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Pinar Alper
- ELIXIR-Luxembourg, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | | | | | | | - Matthew Brush
- University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Tony Burdett
- European Molecular Biology Laboratory—European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Hayley Clissold
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Stacey Donnelly
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stephanie O.M. Dyke
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Department of Neurology & Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Mallory A. Freeberg
- European Molecular Biology Laboratory—European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | | | - Chihiro Hata
- Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Japan
| | - Petr Holub
- BBMRI-ERIC, AT and Masaryk University, Brno, Czech Republic
| | | | - Aina Jene
- Centre de Regulació Genòmica (CRG), Barcelona, Spain
| | - Minae Kawashima
- National Bioscience Database Center, Japan Science and Technology Agency, Tokyo, Japan
| | - Shuichi Kawashima
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Japan
| | | | - Irene Kyomugisha
- Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Haoyuan Li
- Canada’s Michael Smith Genome Sciences Centre, Vancouver, BC, Canada
| | - Mikael Linden
- ELIXIR-Finland, CSC - IT Center for Science Ltd, Espoo, Finland
| | | | | | - Nicola Mulder
- Computational Biology Division, IDM, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Jean Muller
- Laboratoire de Génétique Médicale, Institut de Génétique Médicale d’Alsace, INSERM U1112, Université; de Strasbourg, Strasbourg, France,Laboratoire de Diagnostic Génétique, Institut de Génétique Médicale d’Alsace, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Satoshi Nagaie
- Tohoku Medical Megabank Organization (ToMMo), Tohoku University, Sendai, Japan
| | - Jamal Nasir
- Department of Life Sciences, University of Northampton, Northampton, UK
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization (ToMMo), Tohoku University, Sendai, Japan
| | - Vivian Ota Wang
- Office of Data Sharing, National Cancer Institute, NIH, Rockville, MD, USA
| | | | | | - Helen Parkinson
- European Molecular Biology Laboratory—European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Anthony A. Philippakis
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Fabian Prasser
- Berlin Institute of Health at Charité—Universitätsmedizin Berlin, Berlin, Germany
| | - Jordi Rambla
- Centre de Regulació Genòmica (CRG), Barcelona, Spain
| | - Kathy Reinold
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Gregory A. Rushton
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Andrea Saltzman
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Heidi J. Sofia
- National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - John D. Spalding
- European Molecular Biology Laboratory—European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Morris A. Swertz
- Genomics Coordination Center, Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Esther J. van Enckevort
- Genomics Coordination Center, Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Susheel Varma
- Health Data Research UK, Gibbs Building, 215 Euston Road, London NW1 2BE, UK
| | | | | | | | - Lyndon Zass
- Computational Biology Division, IDM, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | | | | | - Mélanie Courtot
- European Molecular Biology Laboratory—European Bioinformatics Institute (EMBL-EBI), Hinxton, UK,Corresponding author
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6
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Nicol D, Chalmers D, Critchley C, Eckstein L, Nielsen J, Otlowski M. Australian Perspectives on the Ethical and Regulatory Considerations for Responsible Data Sharing in Response to the COVID-19 Pandemic. J Law Med 2020; 27:829-838. [PMID: 32880401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
As the rush to understand and find solutions to the coronavirus disease 2019 pandemic continues, it is timely to re-examine the legal, social and ethical drivers for sharing health-related data from individuals around the globe. International collaboration and data sharing will be essential to the research effort. This raises the question of whether the urgent imperative to find therapies and vaccines may justify some temporary rebalancing of existing ethical and regulatory standards. The Global Alliance for Genomic Health is playing a leading role in collecting information about national approaches to these challenging questions. In this section, we examine some of the initiatives being taken in Australia against this global backdrop.
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Affiliation(s)
- Dianne Nicol
- Centre for Law and Genetics, Law Faculty, University of Tasmania
| | - Don Chalmers
- Centre for Law and Genetics, Law Faculty, University of Tasmania
| | - Christine Critchley
- Centre for Law and Genetics, Law Faculty, University of Tasmania; Swinburne University of Technology
| | - Lisa Eckstein
- Centre for Law and Genetics, Law Faculty, University of Tasmania
| | - Jane Nielsen
- Centre for Law and Genetics, Law Faculty, University of Tasmania
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7
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Sempéré G, Pétel A, Rouard M, Frouin J, Hueber Y, De Bellis F, Larmande P. Gigwa v2-Extended and improved genotype investigator. Gigascience 2019; 8:5488103. [PMID: 31077313 PMCID: PMC6511067 DOI: 10.1093/gigascience/giz051] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 02/19/2019] [Accepted: 04/08/2019] [Indexed: 11/19/2022] Open
Abstract
Background The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution. Results Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data). Conclusions This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.
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Affiliation(s)
- Guilhem Sempéré
- Centre de coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), UMR INTERTRYP, F-34398 Montpellier, France.,South Green Bioinformatics Platform, Bioversity, CIRAD, Institut National de la Recherche Agronomique (INRA), IRD, Montpellier, France.,INTERTRYP, Univ Montpellier, CIRAD, Institut de Recherche pour le Développpement (IRD), Montpellier, France
| | - Adrien Pétel
- South Green Bioinformatics Platform, Bioversity, CIRAD, Institut National de la Recherche Agronomique (INRA), IRD, Montpellier, France.,DIADE, Univ Montpellier, IRD, 911 Avenue Agropolis, 34394 Montpellier, France
| | - Mathieu Rouard
- South Green Bioinformatics Platform, Bioversity, CIRAD, Institut National de la Recherche Agronomique (INRA), IRD, Montpellier, France.,Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier Cedex 5, France
| | - Julien Frouin
- CIRAD, UMR AGAP, F-34398 Montpellier, France.,AGAP, Univ Montpellier, CIRAD, INRA, Institut national d'études supérieures agronomiques de Montpellier (Montpellier SupAgro), Montpellier, France
| | - Yann Hueber
- South Green Bioinformatics Platform, Bioversity, CIRAD, Institut National de la Recherche Agronomique (INRA), IRD, Montpellier, France.,Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier Cedex 5, France
| | - Fabien De Bellis
- CIRAD, UMR AGAP, F-34398 Montpellier, France.,AGAP, Univ Montpellier, CIRAD, INRA, Institut national d'études supérieures agronomiques de Montpellier (Montpellier SupAgro), Montpellier, France
| | - Pierre Larmande
- South Green Bioinformatics Platform, Bioversity, CIRAD, Institut National de la Recherche Agronomique (INRA), IRD, Montpellier, France.,DIADE, Univ Montpellier, IRD, 911 Avenue Agropolis, 34394 Montpellier, France
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8
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Linden M, Prochazka M, Lappalainen I, Bucik D, Vyskocil P, Kuba M, Silén S, Belmann P, Sczyrba A, Newhouse S, Matyska L, Nyrönen T. Common ELIXIR Service for Researcher Authentication and Authorisation. F1000Res 2018; 7:ELIXIR-1199. [PMID: 30254736 PMCID: PMC6124379 DOI: 10.12688/f1000research.15161.1] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/17/2018] [Indexed: 01/08/2023] Open
Abstract
A common Authentication and Authorisation Infrastructure (AAI) that would allow single sign-on to services has been identified as a key enabler for European bioinformatics. ELIXIR AAI is an ELIXIR service portfolio for authenticating researchers to ELIXIR services and assisting these services on user privileges during research usage. It relieves the scientific service providers from managing the user identities and authorisation themselves, enables the researcher to have a single set of credentials to all ELIXIR services and supports meeting the requirements imposed by the data protection laws. ELIXIR AAI was launched in late 2016 and is part of the ELIXIR Compute platform portfolio. By the end of 2017 the number of users reached 1000, while the number of relying scientific services was 36. This paper presents the requirements and design of the ELIXIR AAI and the policies related to its use, and how it can be used for serving some example services, such as document management, social media, data discovery, human data access, cloud compute and training services.
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Affiliation(s)
| | | | | | | | | | | | - Sami Silén
- CSC - IT Center for Science, Espoo, Finland
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9
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Abstract
Over its 30 or so years of existence, the genomic commons-the worldwide collection of publicly accessible repositories of human and nonhuman genomic data-has enjoyed remarkable, perhaps unprecedented, success. Thanks to the rapid public data release policies initiated by the Human Genome Project, free access to a vast array of scientific data is now the norm, not only in genomics, but in scientific disciplines of all descriptions. And far from being a monolithic creation of bureaucratic fiat, the genomic commons is an exemplar of polycentric, multistakeholder governance. But like all dynamic and rapidly evolving systems, the genomic commons is not without its challenges. Issues involving scientific priority, intellectual property, individual privacy, and informed consent, in an environment of data sets of exponentially expanding size and complexity, must be addressed in the near term. In this review, we describe the characteristics and unique history of the genomic commons, then address some of the trends, challenges, and opportunities that we envision for this valuable public resource in the years to come.
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Affiliation(s)
- Jorge L Contreras
- S.J. Quinney College of Law and School of Medicine, University of Utah, Salt Lake City, Utah 84112, USA;
| | - Bartha M Knoppers
- Centre of Genomics and Policy and Department of Medicine, McGill University, Montreal, Quebec H3A 0G1, Canada;
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10
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Abstract
Genomic and medical data sharing is pivotal if the promise of genomic medicine is to be fully realised. Social scientists working in the genomics arena ask the public 'how is the technology working for you?' Empirical studies on attitudes, values and beliefs are incredibly valuable; they offer a voice from those who are, or will be, directly affected. This is paramount if personalised medicine is to be truly personal. An International attitude study, Your DNA, Your Say, uses film to provide background information and an online survey to gather public views on donating one's own personal DNA and medical data for use by others. In this paper the rationale to the project is introduced together with an overview of the survey and film design. The project has been translated into multiple languages and the results will be used in policy for the Global Alliance for Genomics and Health.
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Affiliation(s)
- Anna Middleton
- Society and Ethics Research, Connecting Science, Wellcome Genome Campus, Cambridge
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11
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Buske OJ, Schiettecatte F, Hutton B, Dumitriu S, Misyura A, Huang L, Hartley T, Girdea M, Sobreira N, Mungall C, Brudno M. The Matchmaker Exchange API: automating patient matching through the exchange of structured phenotypic and genotypic profiles. Hum Mutat 2016; 36:922-7. [PMID: 26255989 DOI: 10.1002/humu.22850] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Accepted: 07/24/2015] [Indexed: 01/28/2023]
Abstract
Despite the increasing prevalence of clinical sequencing, the difficulty of identifying additional affected families is a key obstacle to solving many rare diseases. There may only be a handful of similar patients worldwide, and their data may be stored in diverse clinical and research databases. Computational methods are necessary to enable finding similar patients across the growing number of patient repositories and registries. We present the Matchmaker Exchange Application Programming Interface (MME API), a protocol and data format for exchanging phenotype and genotype profiles to enable matchmaking among patient databases, facilitate the identification of additional cohorts, and increase the rate with which rare diseases can be researched and diagnosed. We designed the API to be straightforward and flexible in order to simplify its adoption on a large number of data types and workflows. We also provide a public test data set, curated from the literature, to facilitate implementation of the API and development of new matching algorithms. The initial version of the API has been successfully implemented by three members of the Matchmaker Exchange and was immediately able to reproduce previously identified matches and generate several new leads currently being validated. The API is available at https://github.com/ga4gh/mme-apis.
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Affiliation(s)
- Orion J Buske
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Canada.,Department of Computer Science, University of Toronto, Toronto, Canada.,Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada
| | | | | | - Sergiu Dumitriu
- Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada
| | - Andriy Misyura
- Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada
| | - Lijia Huang
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Taila Hartley
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Marta Girdea
- Department of Computer Science, University of Toronto, Toronto, Canada.,Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada
| | - Nara Sobreira
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Chris Mungall
- Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California
| | - Michael Brudno
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Canada.,Department of Computer Science, University of Toronto, Toronto, Canada.,Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada
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12
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Abstract
The practical realization of genomics has meant a growing realization that variant interpretation is a major barrier to practical use of DNA sequence data. The late Professor Dick Cotton devoted his life to innovation in molecular genetics and was a prime mover in the international response to the need to understand the "variome." His leadership resulted in the launch first of the Human Genetic Variation Society and then, in 2006, an international agreement to launch the Human Variome Project (HVP), aimed at data integration enabled by standards and infrastructure of the databases of variants being identified in families with a range of inherited disorders. The project attracted a network of affiliates across 81 countries and earned formal recognition by UNESCO, which now hosts its biennial meetings. It has also signed a Memorandum of Understanding with the World Health Organization. Future progress will depend on longer term secure funding and integration with the efforts of the genomics community where the rapid advances in sequencing technology have enabled variant capture on a previously unimaginable scale. Efforts are underway to integrate the efforts of HVP with those of the Global Alliance for Genomics and Health to provide a lasting legacy of Dick Cotton's vision.
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Affiliation(s)
- John Burn
- Newcastle University - Institute of Genetic Medicine, International Centre for Life Central Parkway, Newcastle upon Tyne, United Kingdom of Great Britain and Northern Ireland
| | - Michael Watson
- American College of Medical Genetics and Genomics, Bethesda, Maryland
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