The generation of functional genomics data by next-generation sequencing has increased greatly in the past decade. Broad sharing of these data is essential for research advancement but poses notable privacy challenges, some of which are analogous to those that occur when sharing genetic variant data. However, there are also unique privacy challenges that arise from cryptic information leakage during the processing and summarization of functional genomics data from raw reads to derived quantities, such as gene expression values. Here, we review these challenges and present potential solutions for mitigating privacy risks while allowing broad data dissemination and analysis.
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This study was supported by grants from the US National Institutes of Health (R01 HG010749 to M.B.G. and K99 HG010909 to G.G.). This work is also supported by the A.L. Williams Professorship Fund.
The authors declare no competing interests.
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Gürsoy, G., Li, T., Liu, S. et al. Functional genomics data: privacy risk assessment and technological mitigation. Nat Rev Genet 23, 245–258 (2022). https://doi.org/10.1038/s41576-021-00428-7