Haplotype-based membership inference from summary genomic data.

Haplotype-based membership inference from summary genomic data.
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DOI:
10.1093/bioinformatics/btab305
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发表时间:
2021-07-12
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
通讯作者:
Tang H
Tang H
中科院分区:
其他
文献类型:
--
作者:
Bu D;Wang X;Tang H

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人类基因组数据的可用性,以及处理这些数据的能力的增强,正在导致生物医学科学和工程领域的变革性技术进步。然而,由于隐私问题,这些数据的公开传播一直很困难。具体来说,研究表明,病例组中人类受试者的存在可以从该组共享的汇总统计数据中推断出来,例如等位基因频率,甚至是该组中遗传变异的存在/不存在(例如由Beacon项目共享)。这些方法依赖于目标基因组的可用性,即目标人类受试者的DNA谱,因此通常被称为隶属推理方法。在这篇文章中,我们证明了单倍型,即在人类基因组数据库中显示强遗传联系的单核苷酸变异(snv)序列,可以在不使用目标基因组的情况下从基因组数据的总结中推断出来。此外,数据库中没有出现的新单倍型可以仅从基因组数据集中的等位基因频率重建。这些重建的单倍型可用于基于单倍型的隶属推理算法,以比基于snv的现有方法更有效地识别病例组中的目标受试者。成员推理算法的实现可在https://github.com/diybu/Haplotype-based-membership-inferences上获得。
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. 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. The implementation of the membership inference algorithms is available at https://github.com/diybu/Haplotype-based-membership-inferences.
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