Identifying genetic relatives without compromising privacy
- Dan He1,4,
- Nicholas A. Furlotte1,4,
- Farhad Hormozdiari1,
- Jong Wha J. Joo2,
- Akshay Wadia1,
- Rafail Ostrovsky1,5,
- Amit Sahai1,5 and
- Eleazar Eskin1,3,5,6
- 1Department of Computer Science, University of California, Los Angeles, Los Angeles, California 90095,USA;
- 2Interdepartmental Bioinformatics PhD Program, University of California, Los Angeles, California 90095, USA;
- 3Department of Human Genetics, University of California, Los Angeles, Los Angeles, California 90095, USA
Abstract
The development of high-throughput genomic technologies has impacted many areas of genetic research. While many applications of these technologies focus on the discovery of genes involved in disease from population samples, applications of genomic technologies to an individual’s genome or personal genomics have recently gained much interest. One such application is the identification of relatives from genetic data. In this application, genetic information from a set of individuals is collected in a database, and each pair of individuals is compared in order to identify genetic relatives. An inherent issue that arises in the identification of relatives is privacy. In this article, we propose a method for identifying genetic relatives without compromising privacy by taking advantage of novel cryptographic techniques customized for secure and private comparison of genetic information. We demonstrate the utility of these techniques by allowing a pair of individuals to discover whether or not they are related without compromising their genetic information or revealing it to a third party. The idea is that individuals only share enough special-purpose cryptographically protected information with each other to identify whether or not they are relatives, but not enough to expose any information about their genomes. We show in HapMap and 1000 Genomes data that our method can recover first- and second-order genetic relationships and, through simulations, show that our method can identify relationships as distant as third cousins while preserving privacy.
Footnotes
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↵6 Corresponding author
E-mail eeskin{at}cs.ucla.edu
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Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.153346.112.
- Received December 8, 2012.
- Accepted January 24, 2014.
This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported), as described at http://creativecommons.org/licenses/by-nc/3.0/.
