PT  - JOURNAL ARTICLE
AU  - Erlich, Yaniv
TI  - Major flaws in "Identification of individuals by trait prediction using whole-genome"
DP  - 2017 Sep 06
TA  - bioRxiv
4099  - http://biorxiv.org/content/early/2017/09/06/185330.short
4100  - http://biorxiv.org/content/early/2017/09/06/185330.full
AB  - Genetic privacy is an area of active research. While it is important to identify new risks, it is equally crucial to supply policymakers with accurate information based on scientific evidence. Recently, Lippert et al. (PNAS, 2017) investigated the status of genetic privacy using trait-predictions from whole genome sequencing. The authors sequenced a cohort of about 1000 individuals and collected a range of demographic, visible, and digital traits such as age, sex, height, face morphology, and a voice signature. They attempted to use the genetic features in order to predict those traits and re-identify the individuals from small pool using the trait predictions. Here, I report major flaws in the Lippert et al. manuscript. In short, the authors' technique performs similarly to a simple baseline procedure, does not utilize the power of whole genome markers, uses technically wrong metrics, and finally does not really identify anyone.