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The Influence of Relatives on the Efficiency and Error Rate of Familial Searching

Overview of attention for article published in PLOS ONE, August 2013
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Title
The Influence of Relatives on the Efficiency and Error Rate of Familial Searching
Published in
PLOS ONE, August 2013
DOI 10.1371/journal.pone.0070495
Pubmed ID
Authors

Rori V. Rohlfs, Erin Murphy, Yun S. Song, Montgomery Slatkin

Abstract

We investigate the consequences of adopting the criteria used by the state of California, as described by Myers et al. (2011), for conducting familial searches. We carried out a simulation study of randomly generated profiles of related and unrelated individuals with 13-locus CODIS genotypes and YFiler® Y-chromosome haplotypes, on which the Myers protocol for relative identification was carried out. For Y-chromosome sharing first degree relatives, the Myers protocol has a high probability (80~99%) of identifying their relationship. For unrelated individuals, there is a low probability that an unrelated person in the database will be identified as a first-degree relative. For more distant Y-haplotype sharing relatives (half-siblings, first cousins, half-first cousins or second cousins) there is a substantial probability that the more distant relative will be incorrectly identified as a first-degree relative. For example, there is a 3~18% probability that a first cousin will be identified as a full sibling, with the probability depending on the population background. Although the California familial search policy is likely to identify a first degree relative if his profile is in the database, and it poses little risk of falsely identifying an unrelated individual in a database as a first-degree relative, there is a substantial risk of falsely identifying a more distant Y-haplotype sharing relative in the database as a first-degree relative, with the consequence that their immediate family may become the target for further investigation. This risk falls disproportionately on those ethnic groups that are currently overrepresented in state and federal databases.

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Geographical breakdown

Country Count As %
United States 2 4%
Netherlands 1 2%
Australia 1 2%
Unknown 44 92%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 19%
Student > Ph. D. Student 8 17%
Student > Master 8 17%
Researcher 7 15%
Professor 3 6%
Other 8 17%
Unknown 5 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 31%
Agricultural and Biological Sciences 13 27%
Social Sciences 6 13%
Mathematics 2 4%
Medicine and Dentistry 2 4%
Other 5 10%
Unknown 5 10%