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In the UK, genomic health data is being generated in three major contexts: the healthcare system (based on clinical indication), in large scale research programmes, and for purchasers of direct-to-consumer genetic tests. The recently delivered hybrid clinical/research programme, 100,000 Genomes Project set the scene for a new Genomic Medicine Service, through which the National Health Service aims to deliver consistent and equitable care informed by genomics, while providing data to inform academic and industry research and development. In parallel, a large scale research study, Our Future Health, has UK Government and Industry investment and aims to recruit 5 million volunteers to support research intended to improve early detection, risk stratification, and early intervention for chronic diseases. To explore how current models of genomic health data generation intersect, and to understand clinical, ethical, legal, policy and social issues arising from this intersection, we conducted a series of five multidisciplinary panel discussions attended by 28 invited stakeholders. Meetings were recorded and transcribed. We present a summary of issues identified: genomic test attributes; reasons for generating genomic health data; individuals' motivation to seek genomic data; health service impacts; role of genetic counseling; equity; data uses and security; consent; governance and regulation. We conclude with some suggestions for policy consideration.

Patient genomes are interpretable only in the context of other genomes. However, privacy concerns over genetic data oftentimes deter individuals from contributing their genomes to scientific studies and prevent researchers from sharing their data with the scientific community. In this talk, I will describe how we can leverage secure multiparty computation techniques from modern cryptography to perform useful scientific computations on genomic data while protecting the privacy of the participants' genomes. In multiple real scenarios, our methods successfully identified the disease-causing genes and even discovered previously unrecognized disease genes, all while keeping nearly all of the participants' most sensitive genomic information private. We believe that our techniques will help make currently restricted data more readily available to the scientific community and enable individuals to contribute their genomes to a study without compromising their personal privacy.
The material from this talk is based on joint works with Gill Bejerano, Bonnie Berger, Johannes A. Birgmeier, Dan Boneh, Hyunghoon Cho, and Karthik A. Jagadeesh.

Genomic global positioning system (GPS) applies the multilateration technique commonly used in the GPS to genomic data. In the framework we present here, investigators calculate genetic distances from their samples to reference samples, which are from data held in the public domain, and share this information with others. This sharing enables certain types of genomic analysis, such as identifying sample overlaps and close relatives, decomposing ancestry, and mapping of geographical origin without disclosing personal genomes. Thus, our method can be seen as a balance between open data sharing and privacy protection. ; This research was supported by the National Research Foundation of Korea (NRF) grant (grant number 2019R1A2C2002608) and the Bio & Medical Technology Development Program of the NRF (grant number 2017M3A9B6061852) funded by the Korean government, Ministry of Science and ICT. E.E. was supported by National Science Foundation grants 0513612, 0731455, 0729049, 0916676, 1065276, 1302448, 1320589, 1331176, and 1815624, and National Institutes of Health grants K25-HL080079, U01- DA024417, P01-HL30568, P01-HL28481, R01-GM083198, R01-ES021801, R01- MH101782, and R01-ES022282. E.E. was supported in part by the NIH BD2K award, U54EB020403. We acknowledge the support of the NINDS Informatics Center for Neurogenetics and Neurogenomics (P30 NS062691).

Rapid advances in microarray and sequencing technologies are making genotyping and genome sequencing more affordable and readily available. There is an expectation that genomic sequencing technologies improve personalized diagnosis and personalized drug therapy. Concurrently, provision of direct-to-consumer genetic testing by commercial providers has enabled individuals' direct access to their genomic data. The expanded availability of genomic data is perceived as influencing the relationship between the various parties involved including healthcare professionals, researchers, patients, individuals, families, industry, and government. This results in a need to revisit their roles and responsibilities. In a 1-day agenda-setting meeting organized by the COST Action IS1303 "Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives," participants discussed the main challenges associated with the expanded availability of genomic information, with a specific focus on public-private partnerships, and provided an outline from which to discuss in detail the identified challenges. This paper summarizes the points raised at this meeting in five main parts and highlights the key cross-cutting themes. In light of the increasing availability of genomic information, it is expected that this paper will provide timely direction for future research and policy making in this area.

As genomic researchers are urged to openly share generated sequence data with other researchers, it is important to examine the utility of informed consent documents and processes, particularly as these relate to participants' engagement with and recall of the information presented to them, their objective or subjective understanding of the key elements of genomic research (e.g., data sharing), as well as how these factors influence or mediate the decisions they make. We conducted a randomized trial of three experimental informed consent documents (ICDs) with participants (n = 229) being recruited to genomic research studies; each document afforded varying control over breadth of release of genetic information. Recall and understanding, their impact on data sharing decisions, and comfort in decision making were assessed in a follow-up structured interview. Over 25% did not remember signing an ICD to participate in a genomic study, and the majority (54%) could not correctly identify with whom they had agreed to share their genomic data. However, participants felt that they understood enough to make an informed decision, and lack of recall did not impact final data sharing decisions or satisfaction with participation. These findings raise questions about the types of information participants need in order to provide valid informed consent, and whether subjective understanding and comfort with decision making are sufficient to satisfy the ethical principle of respect for persons.

Globally, 15,521 animal species are listed as threatened by the International Union for the Conservation of Nature, and of these less than 3% have genomic resources that can inform conservation management. To combat this, global genome initiatives are developing genomic resources, yet production of a reference genome alone does not conserve a species. The reference genome allows us to develop a suite of tools to understand both genome-wide and functional diversity within and between species. Conservation practitioners can use these tools to inform their decision-making. But, at present there is an implementation gap between the release of genome information and the use of genomic data in applied conservation by conservation practitioners. In May 2020, we launched the Threatened Species Initiative and brought a consortium of genome biologists, population biologists, bioinformaticians, population geneticists, and ecologists together with conservation agencies across Australia, including government, zoos, and nongovernment organizations. Our objective is to create a foundation of genomic data to advance our understanding of key Australian threatened species, and ultimately empower conservation practitioners to access and apply genomic data to their decision-making processes through a web-based portal. Currently, we are developing genomic resources for 61 threatened species from a range of taxa, across Australia, with more than 130 collaborators from government, academia, and conservation organizations. Developed in direct consultation with government threatened-species managers and other conservation practitioners, herein we present our framework for meeting their needs and our systematic approach to integrating genomics into threatened species recovery.

Rapid advances in microarray and sequencing technologies are making genotyping and genome sequencing more affordable and readily available. There is an expectation that genomic sequencing technologies improve personalized diagnosis and personalized drug therapy. Concurrently, provision of direct-to-consumer genetic testing by commercial providers has enabled individuals' direct access to their genomic data. The expanded availability of genomic data is perceived as influencing the relationship between the various parties involved including healthcare professionals, researchers, patients, individuals, families, industry, and government. This results in a need to revisit their roles and responsibilities. In a 1-day agenda-setting meeting organized by the COST Action IS1303 "Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives," participants discussed the main challenges associated with the expanded availability of genomic information, with a specific focus on public-private partnerships, and provided an outline from which to discuss in detail the identified challenges. This paper summarizes the points raised at this meeting in five main parts and highlights the key cross-cutting themes. In light of the increasing availability of genomic information, it is expected that this paper will provide timely direction for future research and policy making in this area. ; info:eu-repo/semantics/publishedVersion

Rapid advances in microarray and sequencing technologies are making genotyping and genome sequencing more affordable and readily available. There is an expectation that genomic sequencing technologies improve personalized diagnosis and personalized drug therapy. Concurrently, provision of direct-to-consumer genetic testing by commercial providers has enabled individuals' direct access to their genomic data. The expanded availability of genomic data is perceived as influencing the relationship between the various parties involved including healthcare professionals, researchers, patients, individuals, families, industry, and government. This results in a need to revisit their roles and responsibilities. In a 1-day agenda-setting meeting organized by the COST Action IS1303 "Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives," participants discussed the main challenges associated with the expanded availability of genomic information, with a specific focus on public-private partnerships, and provided an outline from which to discuss in detail the identified challenges. This paper summarizes the points raised at this meeting in five main parts and highlights the key cross-cutting themes. In light of the increasing availability of genomic information, it is expected that this paper will provide timely direction for future research and policy making in this area.

© The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ; [EN] Background: The integrative analysis of multiple genomics data often requires that genome coordinates-based signals have to be associated with proximal genes. The relative location of a genomic region with respect to the gene (gene area) is important for functional data interpretation; hence algorithms that match regions to genes should be able to deliver insight into this information. Results: In this work we review the tools that are publicly available for making region-to-gene associations. We also present a novel method, RGmatch, a flexible and easy-to-use Python tool that computes associations either at the gene, transcript, or exon level, applying a set of rules to annotate each region-gene association with the region location within the gene. RGmatch can be applied to any organism as long as genome annotation is available. Furthermore, we qualitatively and quantitatively compare RGmatch to other tools. Conclusions: RGmatch simplifies the association of a genomic region with its closest gene. At the same time, it is a powerful tool because the rules used to annotate these associations are very easy to modify according to the researcher's specific interests. Some important differences between RGmatch and other similar tools already in existence are RGmatch's flexibility, its wide range of user options, compatibility with any annotatable organism, and its comprehensive and user-friendly output. ; The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under the grant agreement 306000 and the MINECO (Economy and ...

The Human Genome Project and related projects have resulted in the development of a number of new experimental and analytic tools for use in genomic and proteomic research. In the area of toxicogenomics, researchers are concerned with how genes react to exposure to certain chemicals. The United States Air Force is interested in the effect of exposure to mission-essential chemicals. Although military personnel may come into contact with chemicals such as hydrazine, risk assessment is usually very limited. On the genomic level, risk assessment is a multi-stop and multi-disciplinary process. The process begins with an experiment that exposes cells to the chemical. Data from the experiment are obtained using gene chips. The data can then be analyzed. This research explores the methods of pre-processing and analyzing data. Several different data sets are used to compare the effectiveness of various clustering algorithms and their implementations. Genomic and proteomic data obtained from a hydrazine exposure experiment are then analyzed. A relationship is established between the genomic and proteomic data sets and is used in further analyses.

Cover -- Contents -- Editor Biographies -- Contributors -- Preface -- Chapter 1: An Introduction to Healthcare Data Analytics -- Part I: Healthcare Data Sources and Basic Analytics -- Chapter 2: Electronic Health Records: A Survey -- Chapter 3: Biomedical Image Analysis -- Chapter 4: Mining of Sensor Data in Healthcare: A Survey -- Chapter 5: Biomedical Signal Analysis -- Chapter 6: Genomic Data Analysis for Personalized Medicine -- Chapter 7: Natural Language Processing and Data Mining for Clinical Text -- Chapter 8: Mining the Biomedical Literature -- Chapter 9: Social Media Analytics for Healthcare -- Part II: Advanced Data Analytics for Healthcare -- Chapter 10: A Review of Clinical Prediction Models -- Chapter 11: Temporal Data Mining for Healthcare Data -- Chapter 12: Visual Analytics for Healthcare -- Chapter 13: Predictive Models for Integrating Clinical and Genomic Data -- Chapter 14: Information Retrieval for Healthcare -- Chapter 15: Privacy-Preserving Data Publishing Methods in Healthcare -- Part III: Applications and Practical Systems for Healthcare -- Chapter 16: Data Analytics for Pervasive Health -- Chapter 17: Fraud Detection in Healthcare -- Chapter 18: Data Analytics for Pharmaceutical Discoveries -- Chapter 19: Clinical Decision Support Systems -- Chapter 20: Computer-Assisted Medical Image Analysis Systems -- Chapter 21: Mobile Imaging and Analytics for Biomedical Data -- Color Inserts -- Back Cover.

There are clear benefits from genomics and health data sharing in research and in therapy for individuals across societies. At the same time, citizens have different expectations and fears about that data sharing. International legislation in relation with research ethics and practice and, particularly, data protection create a particular environment that, as is seen in the articles in part two of this special issue, are crying out for harmonisation both at a procedural but at fundamental conceptual levels. The law of data sharing is pulling in different directions. This paper poses the question, harmonisation, an impossible dream?' and the answer is a qualified no'. The paper reflects on what can be seen in the papers in part two of the special issue. It then identifies three major areas of conceptual uncertainty in the new EU General Data Protection Regulation (not because it has superiority over other jurisdictions, but because it is a recent revision of data protection law that leaves universal conceptual questions unclear). Thereafter, the potential for Artificial Intelligence to meet some of the shortcomings is discussed. The paper ends with a consideration of the conditions under which data sharing harmonisation might be achieved: an understanding of a human rights approach and citizen sensitivities in considering the public interest'; social liberalism as a basis of solidarity; and the profession of researcher'.