Data from: Attacks on genetic privacy via uploads to genealogical databases
Edge, Doc; Coop, Graham (2020), Data from: Attacks on genetic privacy via uploads to genealogical databases, Dryad, Dataset, https://doi.org/10.25338/B8X619
Direct-to-consumer (DTC) genetics services are increasingly popular for genetic genealogy, with tens of millions of customers as of 2019. Several DTC genealogy services allow users to upload their own genetic datasets in order to search for genetic relatives. The statement that a user's uploaded genome shares one or more segments in common with that of a target person in the database---that is, that the two genomes share one or more regions identical by state (IBS)---reveals some information about the genotypes of the target person, particularly if the chromosomal locations of IBS matches are shared with the uploader. Here, we describe several methods by which an adversary who wants to learn the genotypes of people in the database can do so by uploading multiple datasets. Depending on the methods used for IBS matching and the information about IBS segments returned to the user, substantial information about users' genotypes can be revealed with a few hundred uploaded datasets. For example, using a method we call IBS tiling, we estimate that an adversary who uploads approximately 900 publicly available genomes could recover at least one allele at SNP sites across up to 82% of the genome of a median person of European ancestries. In databases that detect IBS segments using unphased genotypes, approximately 100 uploads of falsified datasets can reveal enough genetic information to allow accurate genome-wide imputation of every person in the database. We provide simple-to-implement suggestions that will prevent the exploits we describe and discuss our results in light of recent trends in genetic privacy, including the recent use of uploads to DTC genetic genealogy services by law enforcement.
This dataset contains publicly available genoytpes from 872 people of European ancestries. Of these 872 genotypes, 503 came from the EUR subset of phase 3 of the 1000 Genomes project, downloaded from ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/. The EUR subset includes the following population codes and numbers of people: CEU (Utah residents with Northern and Western European Ancestry, 99 people), FIN (Finnish in Finland, 99 people), GBR (British in England and Scotland, 91 people), IBS (Iberian Population in Spain, 107 people), TSI (Toscani in Italia, 107 people).
The remaining 369 were selected from samples typed on the Human Origins SNP array (Patterson et al., 2012), including 142 genotypes from the Human Genome Diversity Project (Cann et al., 2002). Specifically, we downloaded the Human Origins data from https://reich.hms.harvard.edu/downloadable-genotypes-present-day-and-ancient-dna-data-compiled-published-papers, using the 1240K+HO dataset, version 37.2. The 372 selected people were all contemporary samples chosen according to population labels. We also excluded people from the Human Origins dataset if they appeared in the 1000 Genomes dataset. The populations used for selecting data, along with the number of participants included after excluding 1000 Genomes samples, were as follows: "Adygei" (16), "Albanian" (6), "Basque" (29), "Belarusian" (10), "Bulgarian" (10), "Croatian" (10), "Czech" (10), "English" (0), "Estonian" (10), "Finnish" (0), "French" (61), "Greek" (20), "Hungarian" (20), "Icelandic" (12), "Italian_North" (20), "Italian_South" (4), "Lithuanian" (10), "Maltese" (8), "Mordovian" (10), "Norwegian" (11), "Orcadian" (13), "Romanian" (10), "Russian" (22), "Sardinian" (27), "Scottish" (0), "Sicilian" (11), "Spanish" (0), "Spanish_North" (0), and "Ukrainian" (9). The populations with 0 people included are those for which all the samples in the Human Origins dataset are included in the 1000 Genomes phase 3 panel.
We down-sampled the sequence data from the 1000 Genomes project to include only sites typed by the Human Origins chip. Of the 597,573 SNPs included in the Human Origins dataset, 558,257 sites appeared at the same position in the 1000 Genomes dataset, 557,999 of which appear as biallelic SNPs. For 546,530 of these, both the SNP identifier and position match in 1000 Genomes, and for 544,139 of them, the alleles agreed as well. We merged the dataset at the set of 544,139 SNPs at which SNP identifiers, positions, and alleles matched between the Human Origins and 1000 Genomes datasets.
We used vcftools, bcftools, PLINK, and EIGENSOFT to create the merged file. The script used to create it is available at github.com/mdedge/IBS_privacy/.
This dataset is in gzipped vcf format.
National Institutes of Health, Award: GM108779
National Institutes of Health, Award: GM130050