Privacy considerations for sharing genomics data

Oestreich, Marie; Chen, Dingfan; Schultze, Joachim L.; Fritz, Mario; Becker, Matthias

doi:10.17179/excli2021-4002

Cited by 2 publications

(1 citation statement)

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“…Despite these efforts, the issue of communicating WGS results has proven challenging and has not been solved to date. Moreover, there are privacy considerations when sharing raw sequences across institutes and even sectors in order to prevent risks of privacy breaches ( 22 ).…”

Section: Discussionmentioning

confidence: 99%

Comparing Multiple Locus Variable-Number Tandem Repeat Analyses with Whole-Genome Sequencing as Typing Method for Salmonella Enteritidis Surveillance in The Netherlands, January 2019 to March 2020

et al. 2022

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Section: Discussionmentioning

confidence: 99%

Comparing Multiple Locus Variable-Number Tandem Repeat Analyses with Whole-Genome Sequencing as Typing Method for Salmonella Enteritidis Surveillance in The Netherlands, January 2019 to March 2020

et al. 2022

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Assessing Privacy Vulnerabilities in Genetic Data Sets: Scoping Review

Thomas,

Mackes,

Preuss-Dodhy

et al. 2024

JMIR Bioinform Biotech

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Background Genetic data are widely considered inherently identifiable. However, genetic data sets come in many shapes and sizes, and the feasibility of privacy attacks depends on their specific content. Assessing the reidentification risk of genetic data is complex, yet there is a lack of guidelines or recommendations that support data processors in performing such an evaluation. Objective This study aims to gain a comprehensive understanding of the privacy vulnerabilities of genetic data and create a summary that can guide data processors in assessing the privacy risk of genetic data sets. Methods We conducted a 2-step search, in which we first identified 21 reviews published between 2017 and 2023 on the topic of genomic privacy and then analyzed all references cited in the reviews (n=1645) to identify 42 unique original research studies that demonstrate a privacy attack on genetic data. We then evaluated the type and components of genetic data exploited for these attacks as well as the effort and resources needed for their implementation and their probability of success. Results From our literature review, we derived 9 nonmutually exclusive features of genetic data that are both inherent to any genetic data set and informative about privacy risk: biological modality, experimental assay, data format or level of processing, germline versus somatic variation content, content of single nucleotide polymorphisms, short tandem repeats, aggregated sample measures, structural variants, and rare single nucleotide variants. Conclusions On the basis of our literature review, the evaluation of these 9 features covers the great majority of privacy-critical aspects of genetic data and thus provides a foundation and guidance for assessing genetic data risk.

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Privacy considerations for sharing genomics data

Cited by 2 publications

References 59 publications

Comparing Multiple Locus Variable-Number Tandem Repeat Analyses with Whole-Genome Sequencing as Typing Method for Salmonella Enteritidis Surveillance in The Netherlands, January 2019 to March 2020

Comparing Multiple Locus Variable-Number Tandem Repeat Analyses with Whole-Genome Sequencing as Typing Method for Salmonella Enteritidis Surveillance in The Netherlands, January 2019 to March 2020

Assessing Privacy Vulnerabilities in Genetic Data Sets: Scoping Review

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