Abstract
This chapter discusses how clinical data can be published in a way that prevents re-identification attacks, while supporting the validation of Genome-Wide Association Studies (GWAS). After motivating the problem in Sect. 4.1, we provide an overview of an approach that deals with it [5, 9] in Sects. 4.2 and 4.3. This approach extracts potentially linkable clinical features and modifies them in a way that they can no longer be used to link a genomic sequence to a small number of patients, while preserving the associations between genomic sequences and specific sets of clinical features corresponding to GWAS-related diseases.
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Gkoulalas-Divanis, A., Loukides, G. (2013). Preventing Re-identification While Supporting GWAS. In: Anonymization of Electronic Medical Records to Support Clinical Analysis. SpringerBriefs in Electrical and Computer Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5668-1_4
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DOI: https://doi.org/10.1007/978-1-4614-5668-1_4
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