Haplotype-based membership inference from summary genomic data

Abstract Motivation The availability of human genomic data, together with the enhanced capacity to process them, is leading to transformative technological advances in biomedical science and engineering. However, the public dissemination of such data has been difficult due to privacy concerns. Speci...

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Published inBioinformatics (Oxford, England) Vol. 37; no. Supplement_1; pp. i161 - i168
Main Authors Bu, Diyue, Wang, Xiaofeng, Tang, Haixu
Format Journal Article
LanguageEnglish
Published England Oxford University Press 12.07.2021
Oxford Publishing Limited (England)
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ISSN1367-4803
1367-4811
1367-4811
DOI10.1093/bioinformatics/btab305

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Summary:Abstract Motivation The availability of human genomic data, together with the enhanced capacity to process them, is leading to transformative technological advances in biomedical science and engineering. However, the public dissemination of such data has been difficult due to privacy concerns. Specifically, it has been shown that the presence of a human subject in a case group can be inferred from the shared summary statistics of the group, e.g. the allele frequencies, or even the presence/absence of genetic variants (e.g. shared by the Beacon project) in the group. These methods rely on the availability of the target’s genome, i.e. the DNA profile of a target human subject, and thus are often referred to as the membership inference method. Results In this article, we demonstrate the haplotypes, i.e. the sequence of single nucleotide variations (SNVs) showing strong genetic linkages in human genome databases, may be inferred from the summary of genomic data without using a target’s genome. Furthermore, novel haplotypes that did not appear in the database may be reconstructed solely from the allele frequencies from genomic datasets. These reconstructed haplotypes can be used for a haplotype-based membership inference algorithm to identify target subjects in a case group with greater power than existing methods based on SNVs. Availability and implementation The implementation of the membership inference algorithms is available at https://github.com/diybu/Haplotype-based-membership-inferences.
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ISSN:1367-4803
1367-4811
1367-4811
DOI:10.1093/bioinformatics/btab305