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A Sequence Obfuscation Method for Protecting Personal Genomic Privacy
With the technological advances in recent decades, determining whole genome sequencing of a person has become feasible and affordable. As a result, large-scale individual genomic sequences are produced and collected for genetic medical diagnoses and cancer drug discovery, which, however, simultaneou...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043694/ https://www.ncbi.nlm.nih.gov/pubmed/35495121 http://dx.doi.org/10.3389/fgene.2022.876686 |
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author | Wan, Shibiao Wang, Jieqiong |
author_facet | Wan, Shibiao Wang, Jieqiong |
author_sort | Wan, Shibiao |
collection | PubMed |
description | With the technological advances in recent decades, determining whole genome sequencing of a person has become feasible and affordable. As a result, large-scale individual genomic sequences are produced and collected for genetic medical diagnoses and cancer drug discovery, which, however, simultaneously poses serious challenges to the protection of personal genomic privacy. It is highly urgent to develop methods which make the personal genomic data both utilizable and confidential. Existing genomic privacy-protection methods are either time-consuming for encryption or with low accuracy of data recovery. To tackle these problems, this paper proposes a sequence similarity-based obfuscation method, namely IterMegaBLAST, for fast and reliable protection of personal genomic privacy. Specifically, given a randomly selected sequence from a dataset of genomic sequences, we first use MegaBLAST to find its most similar sequence from the dataset. These two aligned sequences form a cluster, for which an obfuscated sequence was generated via a DNA generalization lattice scheme. These procedures are iteratively performed until all of the sequences in the dataset are clustered and their obfuscated sequences are generated. Experimental results on benchmark datasets demonstrate that under the same degree of anonymity, IterMegaBLAST significantly outperforms existing state-of-the-art approaches in terms of both utility accuracy and time complexity. |
format | Online Article Text |
id | pubmed-9043694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90436942022-04-28 A Sequence Obfuscation Method for Protecting Personal Genomic Privacy Wan, Shibiao Wang, Jieqiong Front Genet Genetics With the technological advances in recent decades, determining whole genome sequencing of a person has become feasible and affordable. As a result, large-scale individual genomic sequences are produced and collected for genetic medical diagnoses and cancer drug discovery, which, however, simultaneously poses serious challenges to the protection of personal genomic privacy. It is highly urgent to develop methods which make the personal genomic data both utilizable and confidential. Existing genomic privacy-protection methods are either time-consuming for encryption or with low accuracy of data recovery. To tackle these problems, this paper proposes a sequence similarity-based obfuscation method, namely IterMegaBLAST, for fast and reliable protection of personal genomic privacy. Specifically, given a randomly selected sequence from a dataset of genomic sequences, we first use MegaBLAST to find its most similar sequence from the dataset. These two aligned sequences form a cluster, for which an obfuscated sequence was generated via a DNA generalization lattice scheme. These procedures are iteratively performed until all of the sequences in the dataset are clustered and their obfuscated sequences are generated. Experimental results on benchmark datasets demonstrate that under the same degree of anonymity, IterMegaBLAST significantly outperforms existing state-of-the-art approaches in terms of both utility accuracy and time complexity. Frontiers Media S.A. 2022-04-13 /pmc/articles/PMC9043694/ /pubmed/35495121 http://dx.doi.org/10.3389/fgene.2022.876686 Text en Copyright © 2022 Wan and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Wan, Shibiao Wang, Jieqiong A Sequence Obfuscation Method for Protecting Personal Genomic Privacy |
title | A Sequence Obfuscation Method for Protecting Personal Genomic Privacy |
title_full | A Sequence Obfuscation Method for Protecting Personal Genomic Privacy |
title_fullStr | A Sequence Obfuscation Method for Protecting Personal Genomic Privacy |
title_full_unstemmed | A Sequence Obfuscation Method for Protecting Personal Genomic Privacy |
title_short | A Sequence Obfuscation Method for Protecting Personal Genomic Privacy |
title_sort | sequence obfuscation method for protecting personal genomic privacy |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043694/ https://www.ncbi.nlm.nih.gov/pubmed/35495121 http://dx.doi.org/10.3389/fgene.2022.876686 |
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