Genetic privacy

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Genetic privacy involves the concept of personal privacy concerning the storing, repurposing, provision to third parties, and displaying of information pertaining to one's genetic information. [1] [2] This concept also encompasses privacy regarding the ability to identify specific individuals by their genetic sequence, and the potential to gain information on specific characteristics about that person via portions of their genetic information, such as their propensity for specific diseases or their immediate or distant ancestry. [3]

Contents

With the public release of genome sequence information of participants in large-scale research studies, questions regarding participant privacy have been raised. In some cases, it has been shown that it is possible to identify previously anonymous participants from large-scale genetic studies that released gene sequence information. [4]

Genetic privacy concerns also arise in the context of criminal law because the government can sometimes overcome criminal suspects' genetic privacy interests and obtain their DNA sample. [5] Due to the shared nature of genetic information between family members, this raises privacy concerns of relatives as well. [6]

As concerns and issues of genetic privacy are raised, regulations and policies have been developed in the United States both at a federal and state level. [7] [8]

Significance of genetic information

In the majority of cases, an individual's genetic sequence is considered unique to that individual. One notable exception to this rule in humans is the case of identical twins, who have nearly identical genome sequences at birth. [9] In the remainder of cases, one's genetic fingerprint is considered specific to a particular person and is regularly used in the identification of individuals in the case of establishing innocence or guilt in legal proceedings via DNA profiling. [10] Specific gene variants one's genetic code, known as alleles, have been shown to have strong predictive effects in the occurrences of diseases, such as the BRCA1 and BRCA2 mutant genes in Breast Cancer and Ovarian Cancer, or PSEN1, PSEN2, and APP genes in early-onset Alzheimer's disease. [11] [12] [13] Additionally, gene sequences are passed down with a regular pattern of inheritance between generations, and can therefore reveal one's ancestry via genealogical DNA testing. Additionally with knowledge of the sequence of one's biological relatives, traits can be compared that allow relationships between individuals, or the lack thereof, to be determined, as is often done in DNA paternity testing. As such, one's genetic code can be used to infer many characteristics about an individual, including many potentially sensitive subjects such as: [14]

Sources of genetic information

Kit for genealogical DNA testing by 23andMe 23andme-testkit.jpg
Kit for genealogical DNA testing by 23andMe

Common specimen types for direct-to-consumer genetic testing are cheek swabs and saliva samples. [15] One of the most popular reasons for at-home genetic testing is to obtain information on an individual's ancestry via genealogical DNA testing and is offered by many companies such as 23andMe, AncestryDNA, Family Tree DNA, or MyHeritage. [16] Other tests are also available which provide consumers with information on genes which influence the risk of specific diseases, such as the risk of developing late-onset Alzheimer's disease or celiac disease. [17]

Risks

Privacy Breaches

Studies have shown that genomic data is not immune to adversary attacks. [3] [18] [19] A study conducted in 2013 revealed vulnerabilities in the security of public databases that contain genetic data. [4] As a result, research subjects could sometimes be identified by their DNA alone. [20] Although reports of premeditated breaches outside of experimental research are disputed, researchers suggest the liability is still important to study. [21]

While accessible genomic data has been pivotal in advancing biomedical research, it also escalates the possibility of exposing sensitive information. [3] [18] [19] [21] [22] A common practice in genomic medicine to protect patient anonymity involves removing patient identifiers. [3] [18] [19] [23] However, de-identified data is not subject to the same privileges as the research subjects. [23] [19] Furthermore, there is an increasing ability to re-identify patients and their genetic relatives from their genetic data. [3] [18] [19] [22]

One study demonstrated re-identification by piecing together genomic data from short tandem repeats (e.g. CODIS), SNP allele frequencies (e.g. ancestry testing), and whole-genome sequencing. [18] They also hypothesize using a patient's genetic information, ancestry testing, and social media to identify relatives. [18] Other studies have echoed the risks associated with linking genomic information with public data like social media, including voter registries, web searches, and personal demographics, [3] or with controlled data, like personal medical records. [19]

There is also controversy regarding the responsibility a DNA testing company has to ensure that leaks and breaches do not happen. [24] Determining who legally owns the genomic data, the company or the individual, is of legal concern. There have been published examples of personal genome information being exploited, as well as indirect identification of family members. [18] [25] Additional privacy concerns, related to, e.g., genetic discrimination, loss of anonymity, and psychological impacts, have been increasingly pointed out by the academic community [25] [26] as well as government agencies. [17]

Law Enforcement

Additionally, for criminal justice and privacy advocates, the use of genetic information in identifying suspects for criminal investigations proves worrisome under the United States Fourth Amendment—especially when an indirect genetic link connects an individual to crime scene evidence. [27] Since 2018, law enforcement officials have been harnessing the power of genetic data to revisit cold cases with DNA evidence. [28] Suspects discovered through this process are not directly identified by the input of their DNA into established criminal databases, like CODIS. Instead, suspects are identified as the result of familial genetic sleuthing by law enforcement, submitting crime scene DNA evidence to genetic database services that link users whose DNA similarity indicates a family connection. [28] [29] Officers can then track the newly identified suspect in person, waiting to collect discarded trash that might carry DNA in order to confirm the match. [28]

Despite the privacy concerns of suspects and their relatives, this procedure is likely to survive Fourth Amendment scrutiny. [6] Much like donors of biological samples in cases of genetic research, [30] [31] criminal suspects do not retain property rights in abandoned waste; they can no longer assert an expectation of privacy in the discarded DNA used to confirm law enforcement suspicions, thereby eliminating their Fourth Amendment protection in that DNA. [6] Additionally, the genetic privacy of relatives is likely irrelevant under current caselaw since Fourth Amendment protection is “personal” to criminal defendants. [6]

Psychological Impact

In a systematic review of perspectives toward genetic privacy, researchers highlight some of the concerns individuals hold regarding their genetic information, such as the potential dangers and effects on themselves and family members. [21] Academics note that participating in biomedical research or genetic testing has implications beyond the participant; it can also reveal information about genetic relatives. [18] [20] [21] [25] The study also found that people expressed concerns as to which body controls their information and if their genetic information could be used against them. [21]

Additionally, the American Society of Human Genetics has expressed issues about genetic tests in children. [32] They infer that testing could lead to negative consequences for the child. For example, if a child's likelihood for adoption was influenced by genetic testing, the child might suffer from self esteem issues. A child's well-being might also suffer due to paternity testing or custody battles that require this type of information. [14]

Regulations

When the access of genetic information is regulated, it can prevent insurance companies and employers from reaching such data. This could avoid issues of discrimination, which oftentimes leaves an individual whose information has been breached without a job or without insurance. [14]

In the United States

Federal Regulation

In the United States, biomedical research containing human subjects is governed by a baseline standard of ethics known as The Common Rule, which aims to protect a subject's privacy by requiring "identifiers" such as name or address to be removed from collected data. [33] A 2012 report by the Presidential Commission for the Study of Bioethical Issues stated, however, that "what constitutes 'identifiable' and 'de-identified' data is fluid and that evolving technologies and the increasing accessibility of data could allow de-identified data to become re-identified". [33] In fact, research has already shown that it is "possible to discover a study participant's identity by cross-referencing research data about him and his DNA sequence … [with] genetic genealogy and public-records databases". [34] This has led to calls for policy-makers to establish consistent guidelines and best practices for the accessibility and usage of individual genomic data collected by researchers. [35]

Privacy protections for genetic research participants were strengthened by provisions of the 21st Century Cures Act (H.R.34) passed on 7 December 2016 for which the American Society of Human Genetics (ASHG) commended Congress, Senator Warren and Senator Enzi. [8] [36] [37]

The Genetic Information Nondiscrimination Act of 2008 (GINA) protects the genetic privacy of the public, including research participants. The passage of GINA makes it illegal for health insurers or employers to request or require genetic information of an individual or of family members (and further prohibits the discriminatory use of such information). [38] This protection does not extend to other forms of insurance such as life insurance. [38]

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) also provides some genetic privacy protections. HIPAA defines health information to include genetic information, [39] which places restrictions on who health providers can share the information with. [40]

State Regulation

Three kinds of laws are frequently associated with genetic privacy: those relating to informed consent and property rights, those preventing insurance discrimination, and those prohibiting employment discrimination. [41] [42] According to the National Human Genome Research Institute, forty-one states have enacted genetic privacy laws as of January 2020. [41] However, those privacy laws vary in the scope of protection offered; while some laws "apply broadly to any person" others apply "narrowly to certain entities such as insurers, employers, or researchers." [41]

Arizona, for example, falls in the former category and offers broad protection. Currently, Arizona's genetic privacy statutes focus on the need for informed consent to create, store, or release genetic testing results, [43] [44] but a pending bill would amend the state genetic privacy law framework to grant exclusive property rights in genetic information derived from genetic testing to all persons tested. [45] In expanding privacy rights by including property rights, the bill would grant persons who undergo genetic testing greater control over their genetic information. Arizona also prohibits insurance and employment discrimination on the basis of genetic testing results. [46] [47]

New York State also has strong legislative measures protecting individuals from genetic discrimination. Section 79-I of the New York Civil Rights Law places strict restrictions on the usage of genetic data. The statute also outlines the proper conditions for consenting to genetic data collection or usage. [48]

California similarly offers a broad range of protection for genetic privacy, but it stops short of granting individuals property rights in their genetic information. While currently enacted legislation focuses on prohibiting genetic discrimination in employment [49] and insurance, [50] a piece of pending legislation would extend genetic privacy rights to provide individuals with greater control over genetic information obtained through direct-to-consumer testing services like 23andMe. [51]

Florida passed House Bill 1189, a DNA privacy law that prohibits insurers from using genetic data, in July 2020. [7]

On the other hand, Mississippi offers few genetic privacy protections beyond those required by the federal government. In the Mississippi Employment Fairness Act, the legislature recognized the applicability of the Genetic Information Nondiscrimination Act, [52] which "prohibit[s] discrimination on the basis of genetic information with respect to health insurance and employment." [53] [54]

Other

To balance data sharing with the need to protect the privacy of research subjects geneticists are considering to move more data behind controlled-access barriers, authorizing trusted users to access the data from many studies, rather than "having to obtain it piecemeal from different studies". [4] [20]

In October 2005, IBM became the world's first major corporation to establish a genetics privacy policy. Its policy prohibits using employees' genetic information in employment decisions. [55]

Breaching techniques

According to a 2014 study by Yaniv Erlich and Arvind Narayanan, genetic privacy breaching techniques fall into three categories: [56]

Identity Tracing

Here the aim is to link between an unknown genome and the concealed identity of the data originator by accumulating quasi-identifiers − residual pieces of information that are embedded in the dataset − and to gradually narrow down the possible individuals that match the combination of these quasi-identifiers.

Attribute Disclosure Attacks via DNA (ADAD)

Here the adversary already has access to the identified DNA sample of the target and to a database that links DNA-derived data to sensitive attributes without explicit identifiers, for example a public database of the genetic study of drug abuse. The ADAD techniques match the DNA data and associate the identity of the target with the sensitive attribute

Completion Techniques

Here the adversary also knows the identity of a genomic dataset but has access only to a sanitized version without sensitive loci. The aim here is to expose the sensitive loci that are not part of the original data.

However, more recent studies have indicated new avenues for breaching genetic privacy:

Phenotype Inferences

Here, the goal is to use readily available phenotype information about an individual, such as physical features (or some combination thereof), to make genetic inferences. As genetic databases grow at unprecedented rates, providing larger and more comprehensive aggregates, the ability to make inferences with more probabilistic certainty greatly increases. Furthermore, the scope of potential inferences grows with expanding datasets. [57] [58]

Safeguards

According to a 2022 study by Zhiyu Wan et al., safeguards for genetic privacy fall into two categories: [59]

Legal safeguards include the Genetic Information Nondiscrimination Act of 2008, the Health Insurance Portability and Accountability Act of 1996, the Common Rule, the US National Institutes of Health (NIH) data sharing policy, European Union’s General Data Protection Regulation (GDPR), US state privacy laws (e.g., California Consumer Privacy Act, California Privacy Rights Act, or Virginia Consumer Data Protection Act), self-regulations (e.g., data use agreements, privacy policies, or terms of service), and informed consents.

Technical Safeguards

Technical safeguards include cryptographic tools, access control, and data perturbation approaches. Specifically, cryptographic approaches include homomorphic encryption, secure multiparty computation, trusted execution environment, and Blockchain, whereas data perturbation approaches include k-anonymity, Beacon services, [60] differential privacy, and synthetic data generation. [61]

See also

Related Research Articles

<span class="mw-page-title-main">Genetic testing</span> Medical test

Genetic testing, also known as DNA testing, is used to identify changes in DNA sequence or chromosome structure. Genetic testing can also include measuring the results of genetic changes, such as RNA analysis as an output of gene expression, or through biochemical analysis to measure specific protein output. In a medical setting, genetic testing can be used to diagnose or rule out suspected genetic disorders, predict risks for specific conditions, or gain information that can be used to customize medical treatments based on an individual's genetic makeup. Genetic testing can also be used to determine biological relatives, such as a child's biological parentage through DNA paternity testing, or be used to broadly predict an individual's ancestry. Genetic testing of plants and animals can be used for similar reasons as in humans, to gain information used for selective breeding, or for efforts to boost genetic diversity in endangered populations.

<span class="mw-page-title-main">Pharmacogenomics</span> Study of the role of the genome in drug response

Pharmacogenomics is the study of the role of the genome in drug response. Its name reflects its combining of pharmacology and genomics. Pharmacogenomics analyzes how the genetic makeup of a patient affects their response to drugs. It deals with the influence of acquired and inherited genetic variation on drug response, by correlating DNA mutations with pharmacokinetic, pharmacodynamic, and/or immunogenic endpoints.

Genetic genealogy is the use of genealogical DNA tests, i.e., DNA profiling and DNA testing, in combination with traditional genealogical methods, to infer genetic relationships between individuals. This application of genetics came to be used by family historians in the 21st century, as DNA tests became affordable. The tests have been promoted by amateur groups, such as surname study groups or regional genealogical groups, as well as research projects such as the Genographic Project.

Genetic discrimination occurs when people treat others differently because they have or are perceived to have a gene mutation(s) that causes or increases the risk of an inherited disorder. It may also refer to any and all discrimination based on the genotype of a person rather than their individual merits, including that related to race, although the latter would be more appropriately included under racial discrimination. Some legal scholars have argued for a more precise and broader definition of genetic discrimination: "Genetic discrimination should be defined as when an individual is subjected to negative treatment, not as a result of the individual's physical manifestation of disease or disability, but solely because of the individual's genetic composition." Genetic Discrimination is considered to have its foundations in genetic determinism and genetic essentialism, and is based on the concept of genism, i.e. distinctive human characteristics and capacities are determined by genes.

<span class="mw-page-title-main">Ancestry-informative marker</span>

In population genetics, an ancestry-informative marker (AIM) is a single-nucleotide polymorphism that exhibits substantially different frequencies between different populations. A set of many AIMs can be used to estimate the proportion of ancestry of an individual derived from each population.

Public health genomics is the use of genomics information to benefit public health. This is visualized as more effective preventive care and disease treatments with better specificity, tailored to the genetic makeup of each patient. According to the Centers for Disease Control and Prevention (U.S.), Public Health genomics is an emerging field of study that assesses the impact of genes and their interaction with behavior, diet and the environment on the population's health.

<span class="mw-page-title-main">Genetic Information Nondiscrimination Act</span>

The Genetic Information Nondiscrimination Act of 2008, is an Act of Congress in the United States designed to prohibit some types of genetic discrimination. The act bars the use of genetic information in health insurance and employment: it prohibits group health plans and health insurers from denying coverage to a healthy individual or charging that person higher premiums based solely on a genetic predisposition to developing a disease in the future, and it bars employers from using individuals' genetic information when making hiring, firing, job placement, or promotion decisions. Senator Ted Kennedy called it the "first major new civil rights bill of the new century." The Act contains amendments to the Employee Retirement Income Security Act of 1974 and the Internal Revenue Code of 1986.

<span class="mw-page-title-main">23andMe</span> American personal genomics company

23andMe Holding Co. is a publicly held personal genomics and biotechnology company based in South San Francisco, California. It is best known for providing a direct-to-consumer genetic testing service in which customers provide a saliva sample that is laboratory analysed, using single nucleotide polymorphism genotyping, to generate reports relating to the customer's ancestry and genetic predispositions to health-related topics. The company's name is derived from the 23 pairs of chromosomes in a diploid human cell.

A DNA database or DNA databank is a database of DNA profiles which can be used in the analysis of genetic diseases, genetic fingerprinting for criminology, or genetic genealogy. DNA databases may be public or private, the largest ones being national DNA databases.

<span class="mw-page-title-main">Biobank</span> Repository of biological samples used for research

A biobank is a type of biorepository that stores biological samples for use in research. Biobanks have become an important resource in medical research, supporting many types of contemporary research like genomics and personalized medicine.

Personal genomics or consumer genetics is the branch of genomics concerned with the sequencing, analysis and interpretation of the genome of an individual. The genotyping stage employs different techniques, including single-nucleotide polymorphism (SNP) analysis chips, or partial or full genome sequencing. Once the genotypes are known, the individual's variations can be compared with the published literature to determine likelihood of trait expression, ancestry inference and disease risk.

<span class="mw-page-title-main">Whole genome sequencing</span> Determining nearly the entirety of the DNA sequence of an organisms genome at a single time

Whole genome sequencing (WGS), also known as full genome sequencing, complete genome sequencing, or entire genome sequencing, is the process of determining the entirety, or nearly the entirety, of the DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.

<span class="mw-page-title-main">Exome sequencing</span> Sequencing of all the exons of a genome

Exome sequencing, also known as whole exome sequencing (WES), is a genomic technique for sequencing all of the protein-coding regions of genes in a genome. It consists of two steps: the first step is to select only the subset of DNA that encodes proteins. These regions are known as exons—humans have about 180,000 exons, constituting about 1% of the human genome, or approximately 30 million base pairs. The second step is to sequence the exonic DNA using any high-throughput DNA sequencing technology.

Privacy for research participants is a concept in research ethics which states that a person in human subject research has a right to privacy when participating in research. Some typical scenarios this would apply to include, or example, a surveyor doing social research conducts an interview with a participant, or a medical researcher in a clinical trial asks for a blood sample from a participant to see if there is a relationship between something which can be measured in blood and a person's health. In both cases, the ideal outcome is that any participant can join the study and neither the researcher nor the study design nor the publication of the study results would ever identify any participant in the study. Thus, the privacy rights of these individuals can be preserved.

openSNP is an open source website where users can share their genetic information. Users upload their genes, including gender, age, eye color, medical history, Fitbit data. With a focus on user patient-led research (PLR), there is potential to redefine the way health research is conducted.

"It promises to be a vital supplement to standard research: it can focus on conditions that are neglected by standard research, such as rare diseases or side effects, and can draw on a broader range of data and deliver outcomes more rapidly. It can also be a way of realising valuable forms of social interaction and support in cases where members of a community conduct PLR together, for example, patients suffering from the same illness."

Elective genetic and genomic testing are DNA tests performed for an individual who does not have an indication for testing. An elective genetic test analyzes selected sites in the human genome while an elective genomic test analyzes the entire human genome. Some elective genetic and genomic tests require a physician to order the test to ensure that individuals understand the risks and benefits of testing as well as the results. Other DNA-based tests, such as a genealogical DNA test do not require a physician's order. Elective testing is generally not paid for by health insurance companies. With the advent of personalized medicine, also called precision medicine, an increasing number of individuals are undertaking elective genetic and genomic testing.

DNA encryption is the process of hiding or perplexing genetic information by a computational method in order to improve genetic privacy in DNA sequencing processes. The human genome is complex and long, but it is very possible to interpret important, and identifying, information from smaller variabilities, rather than reading the entire genome. A whole human genome is a string of 3.2 billion base paired nucleotides, the building blocks of life, but between individuals the genetic variation differs only by 0.5%, an important 0.5% that accounts for all of human diversity, the pathology of different diseases, and ancestral story. Emerging strategies incorporate different methods, such as randomization algorithms and cryptographic approaches, to de-identify the genetic sequence from the individual, and fundamentally, isolate only the necessary information while protecting the rest of the genome from unnecessary inquiry. The priority now is to ascertain which methods are robust, and how policy should ensure the ongoing protection of genetic privacy.

<span class="mw-page-title-main">Charles Rotimi</span> Nigerian geneticist

Charles Nohuoma Rotimi is the Scientific Director of the National Human Genome Research Institute (NHGRI). He joined the National Institutes of Health (NIH) in 2008 as the inaugural Director of the Trans-NIH Center for Research in Genomics and Global Health and was also the chief of the NHGRI's Metabolic, Cardiovascular, and Inflammatory Disease Genomics Branch. He works to ensure that population genetics include genomes from African populations and founded the African Society of Human Genetics in 2003 and was elected its first president. Rotimi was instrumental in the launch of the Human Heredity and Health in Africa (H3Africa) with the NIH and the Wellcome Trust. He was elected to the National Academy of Medicine in 2018.

Human genetic clustering refers to patterns of relative genetic similarity among human individuals and populations, as well as the wide range of scientific and statistical methods used to study this aspect of human genetic variation.

Personalized genomics is the human genetics-derived study of analyzing and interpreting individualized genetic information by genome sequencing to identify genetic variations compared to the library of known sequences. International genetics communities have spared no effort from the past and have gradually cooperated to prosecute research projects to determine DNA sequences of the human genome using DNA sequencing techniques. The methods that are the most commonly used are whole exome sequencing and whole genome sequencing. Both approaches are used to identify genetic variations. Genome sequencing became more cost-effective over time, and made it applicable in the medical field, allowing scientists to understand which genes are attributed to specific diseases.

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  47. ↑ "Ariz. Rev. Stat. Ann. § 41-1463(B)(3) (2019)". Arizona State Legislature. Retrieved May 18, 2020.
  48. ↑ "Confidentiality of records of genetic tests". NY State Senate. 2021-01-09. Retrieved 2021-03-19.
  49. ↑ Cal. Gov't Code § 12940(a) (2019)
  50. ↑ Cal. Gov't Code § 11135 (2019).
  51. ↑ Cal. 2020 AB 2301
  52. ↑ "Miss. Code Ann. 71-15-3 (2018)". Justia. Retrieved May 18, 2020.
  53. ↑ Genetic Information Nondiscrimination Act of 2008, Pub. L. 110-233.
  54. ↑ 153 Cong. Rec. H4083 (Apr. 25, 2007) (statement of Rep. Miller).
  55. ↑ "IBM100 - Pioneering Genetic Privacy". 7 March 2012. Retrieved 2 January 2017.
  56. ↑ Yaniv Erlich; Arvind Narayanan (2013). "Routes for breaching and protecting genetic privacy". arXiv: 1310.3197 [q-bio.GN].
  57. ↑ Bonomi, Luca; Huang, Yingxiang; Ohno-Machado, Lucila (July 2020). "Privacy challenges and research opportunities for genomic data sharing". Nature Genetics. 52 (7): 646–654. doi:10.1038/s41588-020-0651-0. ISSN   1061-4036. PMC   7761157 . PMID   32601475.
  58. ↑ Ayday, Erman; Humbert, Mathias (2017). "Inference Attacks against Kin Genomic Privacy". IEEE Security & Privacy. 15 (5): 29–37. doi:10.1109/MSP.2017.3681052. hdl: 11693/37113 . ISSN   1540-7993. S2CID   7357416.
  59. ↑ Wan, Zhiyu; Hazel, James W.; Clayton, Ellen Wright; Vorobeychik, Yevgeniy; Kantarcioglu, Murat; Malin, Bradley A. (2022-03-04). "Sociotechnical safeguards for genomic data privacy". Nature Reviews Genetics. 23 (7): 429–445. doi:10.1038/s41576-022-00455-y. ISSN   1471-0064. PMC   8896074 . PMID   35246669.
  60. ↑ Fiume, Marc; Cupak, Miroslav; Keenan, Stephen; Rambla, Jordi; de la Torre, Sabela; Dyke, Stephanie O. M.; Brookes, Anthony J.; Carey, Knox; Lloyd, David; Goodhand, Peter; Haeussler, Maximilian (March 2019). "Federated discovery and sharing of genomic data using Beacons". Nature Biotechnology. 37 (3): 220–224. doi:10.1038/s41587-019-0046-x. ISSN   1546-1696. PMC   6728157 . PMID   30833764.
  61. ↑ Yelmen, Burak; Decelle, Aurélien; Ongaro, Linda; Marnetto, Davide; Tallec, Corentin; Montinaro, Francesco; Furtlehner, Cyril; Pagani, Luca; Jay, Flora (2021-02-04). "Creating artificial human genomes using generative neural networks". PLOS Genetics. 17 (2): e1009303. doi:10.1371/journal.pgen.1009303. ISSN   1553-7404. PMC   7861435 . PMID   33539374.

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