@techreport{oai:ipsj.ixsq.nii.ac.jp:00213155,
 author = {Mohammad, Nabil Ahmed and Kana, Shimizu and Mohammad, Nabil Ahmed and Kana, Shimizu},
 issue = {4},
 month = {Sep},
 note = {Genomic data can be used to infer private and sensitive information about individuals, which prevents it from being shared publicly. Despite the use of data de-anonymization techniques, the release of statistical measures from a genomic database can make it vulnerable to privacy-centric attacks. Genotype imputation, a technique developed from statistical genetics has recently found increasing usage in Genome-wide Association Studies (GWAS), where it is used to increase the coverage of genotype information. The privacy-centric nature of genetic information has led to the adoption of database governance that stonewalls it from public-access, limiting the access to information-rich imputation reference datasets. In this research we propose mechanisms through which privately-held imputation reference panels can be released without invalidating data privacy., Genomic data can be used to infer private and sensitive information about individuals, which prevents it from being shared publicly. Despite the use of data de-anonymization techniques, the release of statistical measures from a genomic database can make it vulnerable to privacy-centric attacks. Genotype imputation, a technique developed from statistical genetics has recently found increasing usage in Genome-wide Association Studies (GWAS), where it is used to increase the coverage of genotype information. The privacy-centric nature of genetic information has led to the adoption of database governance that stonewalls it from public-access, limiting the access to information-rich imputation reference datasets. In this research we propose mechanisms through which privately-held imputation reference panels can be released without invalidating data privacy.},
 title = {A Privacy-preserving Reference Panel for Genotype Imputation},
 year = {2021}
}