A Privacy-preserving Reference Panel for Genotype Imputation

• Item type: SIG Technical Reports(1)
• 公開日: 2021-09-23
• タイトル: A Privacy-preserving Reference Panel for Genotype Imputation
• タイトル / 言語: en
• タイトル: A Privacy-preserving Reference Panel for Genotype Imputation
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Department of Computer Science and Communication Engineering, Waseda University
• 著者所属: Department of Computer Science and Communication Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Department of Computer Science and Communication Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Department of Computer Science and Communication Engineering, Waseda University
• 著者名: Mohammad, Nabil Ahmed; Kana, Shimizu
• 著者名(英): Mohammad, Nabil Ahmed; Kana, Shimizu
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: 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.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: 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.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA12055912
• 書誌情報: 研究報告バイオ情報学（BIO）; 巻 2021-BIO-67, 号 4, p. 1-3, 発行日 2021-09-23
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2188-8590
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会