Haplotype-based membership inference from summary genomic data
Author(s) -
Diyue Bu,
Xiaofeng Wang,
Haixu Tang
Publication year - 2021
Publication title -
bioinformatics
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btab305
Subject(s) - haplotype , inference , 1000 genomes project , human genome , genome , genomics , haplotype estimation , computational biology , dna sequencing , computer science , biology , genetics , allele , data mining , single nucleotide polymorphism , artificial intelligence , gene , genotype
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.
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