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A new way to protect privacy in large-scale genome-wide association studies

Motivation: Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown...

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Detalles Bibliográficos
Autores principales: Kamm, Liina, Bogdanov, Dan, Laur, Sven, Vilo, Jaak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3605601/
https://www.ncbi.nlm.nih.gov/pubmed/23413435
http://dx.doi.org/10.1093/bioinformatics/btt066
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author Kamm, Liina
Bogdanov, Dan
Laur, Sven
Vilo, Jaak
author_facet Kamm, Liina
Bogdanov, Dan
Laur, Sven
Vilo, Jaak
author_sort Kamm, Liina
collection PubMed
description Motivation: Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues. Results: We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees. Contact: jaak.vilo@ut.ee Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-36056012013-03-22 A new way to protect privacy in large-scale genome-wide association studies Kamm, Liina Bogdanov, Dan Laur, Sven Vilo, Jaak Bioinformatics Original Papers Motivation: Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues. Results: We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees. Contact: jaak.vilo@ut.ee Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2013-04-01 2013-02-14 /pmc/articles/PMC3605601/ /pubmed/23413435 http://dx.doi.org/10.1093/bioinformatics/btt066 Text en © The Author 2013. Published by Oxford University Press. All rights reserved. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Kamm, Liina
Bogdanov, Dan
Laur, Sven
Vilo, Jaak
A new way to protect privacy in large-scale genome-wide association studies
title A new way to protect privacy in large-scale genome-wide association studies
title_full A new way to protect privacy in large-scale genome-wide association studies
title_fullStr A new way to protect privacy in large-scale genome-wide association studies
title_full_unstemmed A new way to protect privacy in large-scale genome-wide association studies
title_short A new way to protect privacy in large-scale genome-wide association studies
title_sort new way to protect privacy in large-scale genome-wide association studies
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3605601/
https://www.ncbi.nlm.nih.gov/pubmed/23413435
http://dx.doi.org/10.1093/bioinformatics/btt066
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