ENGLISH

Responsible Genomic Data Sharing: Challenges and Approaches

Book information

Publisher
Academic Press
Year
2020
ISBN
0128161973, 9780128161975
Language
english
Format
PDF
Filesize
6 MB (6633633 bytes)
Edition
1
Pages
210\199
Time added
2020-06-23 18:35:56

Description

Responsible Genomic Data Sharing: Challenges and Approaches brings together international experts in genomics research, bioinformatics and digital security who analyze common challenges in genomic data sharing, privacy preserving technologies, and best practices for large-scale genomic data sharing. Practical case studies, including the Global Alliance for Genomics and Health, the Beacon Network, and the Matchmaker Exchange, are discussed in-depth, illuminating pathways forward for new genomic data sharing efforts across research and clinical practice, industry and academia. Cover Responsible Genomic Data Sharing: Challenges and Approaches Copyright Contributors Section I: Privacy challenges in genomic data sharing 1. Criticality of data sharing in genomic research and public views of genomic data sharing 1. Introduction 2. Advancing research and scientific knowledge 3. Importance of genomic data sharing in curing diseases 3.1 Rare disease perspective 3.2 Cancer perspective 3.3 Genome-wide association studies perspective 4. Impact of large-scale data sharing on basic research and discovery 4.1 The International HapMap Project 4.2 1000 Genomes Project 4.3 The Cancer Genome Atlas project 4.4 Encyclopedia of DNA Elements Project 4.5 Genotype-Tissue Expression Project 5. Reproducibility 6. Patient/public perspective References 2. Genomic data access policy models 1. Data-sharing policy developments 2. Open-access policy model 3. Controlled-access policy model 4. Registered-access policy model 5. Ongoing concerns and developments 5.1 Maintaining consent: Consent Codes 5.2 Data-sharing risk assessment: choosing the right access level References 3. Information leaks in genomic data: inference attacks 1. Inference attacks on statistical genomic databases 2. Inference attacks on genomic data-sharing beacons 3. Inference attacks on kin genomic privacy 4. Inference attacks using genotype–phenotype associations 5. Conclusions References 4. Genealogical search using whole-genome genotype profiles 1. Introduction 2. History of personal genetic data 2.1 HapMap 2.2 1000 genomes Project 2.3 UK Biobank and beyond 3. Direct-to-consumer genetic companies 3.1 Early days 3.2 Growth 3.3 Current trends 3.4 GEDMatch and others 4. How to encode genotype information at the genome scale 4.1 Genotype 4.2 Haplotype 4.3 Phasing 4.4 File format 4.4.1 VCF format 4.4.2 DTC format 4.4.3 Compressed format 4.4.3.1 PLINK format (BED) 4.4.3.1 PLINK format (BED) 4.4.3.2 UK Biobank format (BGEN) 4.4.3.2 UK Biobank format (BGEN) 4.4.3.3 GDS format 4.4.3.3 GDS format 4.4.3.4 Population-genetics inspired format: PBWT (BGT) and tree sequence (tsinfer) 4.4.3.4 Population-genetics inspired format: PBWT (BGT) and tree sequence (tsinfer) 5. Identity-by-descent segment and familial relatedness 5.1 Genetic distance 5.2 What is IBD 5.3 Cousin nomenclature 5.4 How IBD is related to family relationships 5.5 Expected IBD family sharing 6. Genealogical search 6.1 What is a genealogy search 6.1.1 Difference between ancestry and genealogy 6.2 Genotype-based method 6.2.1 HIR match 6.3 Haplotype-based method 6.3.1 GERMLINE 6.3.2 PBWT-based method, RaPID and PBWT-query 6.3.3 Refined-IBD 6.4 Benchmarking of IBD detection: runtime, power, and accuracy 7. Practical methods 7.1 Methods used by DTC companies 8. Challenges and unmet needs 8.1 Ancestry bias 8.2 Phasing imperfection 8.3 Benchmarking of genealogical search 9. Privacy concerns 10. Conclusions References Section II: Privacy-preserving techniques for responsible genomic data sharing 5. Homomorphic encryption 1. Overview 1.1 Early ideas 1.2 Homomorphic encryption 1.3 Note about terminology 1.4 Implementations 1.5 Standardization 1.6 Applications 2. Homomorphic encryption 2.1 What is encryption? 2.2 Partially homomorphic encryption 2.3 Mathematical background 2.4 (Ring) Learning With Errors 2.4.1 Learning With Errors 2.4.2 Ring Learning With Errors 2.4.3 Decision problems 2.5 The Brakerski–Fan–Vercauteren scheme 2.5.1 Plaintexts and ciphertexts 2.5.2 Encryption and decryption 2.5.3 Security 2.5.4 Noise 2.5.5 Addition 2.5.6 Multiplication 2.5.7 Relinearization 2.5.8 Implementation complexity 2.6 Computing on encrypted integers 2.7 Batching 2.7.1 Micro-benchmarks 2.8 Approximate arithmetic on encrypted numbers 2.9 Other schemes 2.9.1 Brakerski–Gentry–Vaikuntanathan 2.9.2 Torus FHE 2.9.3 High-precision arithmetic on encrypted integers 3. Applications 3.1 Outsourced storage and computation 3.2 Private prediction 3.3 Private learning 3.4 PSI and PIR 3.5 Biomedical applications 4. Future Outlook 4.1 Complexity 4.2 Usability 4.3 Hardware 5. Conclusions References 6. Secure multi-party computation 1. A brief overview 2. Defining security 3. Protocols 3.1 Oblivious transfer 3.2 Multiplicative triples 3.3 Generic MPC in linear rounds 3.4 Generic MPC in constant rounds 3.5 Pool-based cut-and-choose References 7. Game theory for privacy-preserving sharing of genomic data 1. Introduction 2. Background 3. Membership-inference game 3.1 The game and its solutions 3.2 Limitations of the model 4. Beacon service game 4.1 The game and its solutions 4.2 Limitations of the model 5. Kinship game 5.1 The game and its solutions 5.2 Limitations of the model 6. Re-identification game 6.1 The game and its solutions 6.2 Limitations of the model 7. Discussion 8. Conclusions References 8. Trusted execution environment with Intel SGX 1. Introduction 2. Trusted execution environment 3. Intel Software Guard Extensions 3.1 Hardware architecture 3.1.1 Memory encryption engine and protected memory region 3.1.2 Enclave page cache and SGX data structures 3.1.3 Enclave creation and execution 3.1.4 Enclave paging 3.1.5 Enclave teardown 3.1.6 SGX platform stack 3.1.7 Remote attestation 3.2 Software development 3.3 Security properties 3.4 Performance properties 4. HW-MPC and SGX in cloud 4.1 TEEs in the cloud 4.2 Developing with SGX in the cloud 4.3 Deploying SGX applications 4.4 Open questions on SGX in the cloud 4.5 Putting it all together 5. Outlook References Index Index A B C D E F G H I J K L M N O P Q R S T U V

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