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research article

Simulating the Large-Scale Erosion of Genomic Privacy Over Time

Backes, Michael
•
Berrang, Pascal
•
Humbert, Mathias  
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September 1, 2018
Ieee-Acm Transactions On Computational Biology And Bioinformatics

The dramatically decreasing costs of DNA sequencing have triggered more than a million humans to have their genotypes sequenced. Moreover, these individuals increasingly make their genomic data publicly available, thereby creating privacy threats for themselves and their relatives because of their DNA similarities. More generally, an entity that gains access to a significant fraction of sequenced genotypes might be able to infer even the genomes of unsequenced individuals. In this paper, we propose a simulation-based model for quantifying the impact of continuously sequencing and publicizing personal genomic data on a population's genomic privacy. Our simulation probabilistically models data sharing and takes into account events such as migration and interracial mating. We exemplarily instantiate our simulation with a sample population of 1,000 individuals and evaluate the privacy under multiple settings over 6,000 genomic variants and a subset of phenotype-related variants. Our findings demonstrate that an increasing sharing rate in the future entails a substantial negative effect on the privacy of all older generations. Moreover, we find that mixed populations face a less severe erosion of privacy over time than more homogeneous populations. Finally, we demonstrate that genomic-data sharing can be much more detrimental for the privacy of the phenotype-related variants.

  • Details
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Type
research article
DOI
10.1109/TCBB.2018.2859380
Web of Science ID

WOS:000448910300002

Author(s)
Backes, Michael
Berrang, Pascal
Humbert, Mathias  
Shen, Xiaoyu
Wolf, Verena
Date Issued

2018-09-01

Publisher

IEEE COMPUTER SOC

Published in
Ieee-Acm Transactions On Computational Biology And Bioinformatics
Volume

15

Issue

5

Start page

1405

End page

1412

Subjects

Biochemical Research Methods

•

Computer Science, Interdisciplinary Applications

•

Mathematics, Interdisciplinary Applications

•

Statistics & Probability

•

Biochemistry & Molecular Biology

•

Computer Science

•

Mathematics

•

genomic privacy

•

simulations

•

inference

•

graphical models

•

complex pedigrees

•

genetic analyses

•

genotypes

Note

3rd International Workshop on Genome Privacy and Security (GenoPri), Chicago, IL, Nov 12, 2016

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
ISC  
LDS  
Available on Infoscience
December 13, 2018
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/152441
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