SQUiD: ultra-secure storage and analysis of genetic data for the advancement of precision medicine

Jacob Blindenbach; Jiayi Kang; Seungwan Hong; Caline Karam; Thomas Lehner; Gamze Gürsoy

doi:10.1186/s13059-024-03447-9

SQUiD: ultra-secure storage and analysis of genetic data for the advancement of precision medicine

Genome Biol. 2024 Dec 18;25(1):314. doi: 10.1186/s13059-024-03447-9.

Authors

Jacob Blindenbach^#^{1

2

3}, Jiayi Kang^#⁴, Seungwan Hong^#^{5

6}, Caline Karam³, Thomas Lehner³, Gamze Gürsoy^{7

8

9}

Affiliations

¹ Department of Computer Science, Columbia University, New York, USA.
² Department of Biomedical Informatics, Columbia University, New York, USA.
³ New York Genome Center, New York, USA.
⁴ COSIC, KU Leuven, Leuven, Belgium.
⁵ Department of Biomedical Informatics, Columbia University, New York, USA. [email protected].
⁶ New York Genome Center, New York, USA. [email protected].
⁷ Department of Computer Science, Columbia University, New York, USA. [email protected].
⁸ Department of Biomedical Informatics, Columbia University, New York, USA. [email protected].
⁹ New York Genome Center, New York, USA. [email protected].

^# Contributed equally.

Abstract

Cloud computing allows storing the ever-growing genotype-phenotype datasets crucial for precision medicine. Due to the sensitive nature of this data and varied laws and regulations, additional security measures are needed to ensure data privacy. We develop SQUiD, a secure queryable database for storing and analyzing genotype-phenotype data. SQUiD allows storage and secure querying of data in a low-security, low-cost public cloud using homomorphic encryption in a multi-client setting. We demonstrate SQUiD's practical usability and scalability using synthetic and UK Biobank data.

MeSH terms

Cloud Computing
Computer Security
Databases, Genetic
Humans
Information Storage and Retrieval
Precision Medicine*

Abstract

MeSH terms

Grants and funding