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      Big Data in medical research and EU data protection law: challenges to the consent or anonymise approach

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      Journal: European Journal of Human Genetics
      Publisher: Springer Nature

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          Identifying personal genomes by surname inference.

          Melissa Gymrek, Amy McGuire, David Golan … (2013)
          Sharing sequencing data sets without identifiers has become a common practice in genomics. Here, we report that surnames can be recovered from personal genomes by profiling short tandem repeats on the Y chromosome (Y-STRs) and querying recreational genetic genealogy databases. We show that a combination of a surname with other types of metadata, such as age and state, can be used to triangulate the identity of the target. A key feature of this technique is that it entirely relies on free, publicly accessible Internet resources. We quantitatively analyze the probability of identification for U.S. males. We further demonstrate the feasibility of this technique by tracing back with high probability the identities of multiple participants in public sequencing projects.
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            Biology: The big challenges of big data.

            Vivien Marx (2013)
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              UK biobank data: come and get it.

              Naomi Allen, Cathie Sudlow, Tim Peakman … (2014)
              Article 0 comments Cited 172 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Title: European Journal of Human Genetics
                Abbreviated Title: Eur J Hum Genet
                Publisher: Springer Nature
                ISSN (Print): 1018-4813
                ISSN (Electronic): 1476-5438
                Publication date Created: November 11 2015
                Publication date (Print): November 11 2015
                Volume: 24
                Issue: 7
                Pages: 956-960
                Article
                DOI: 10.1038/ejhg.2015.239
                PMC ID: 5070890
                PubMed ID: 26554881
                SO-VID: d8918c86-4a6a-4a0b-b050-32e36d097ad4
                Copyright © © 2015
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