Collaborative analysis of genomic data: vision and challenges
This addresses privacy and collaboration issues in genomic data analysis for researchers and healthcare, but it is incremental as it builds on existing regulations and techniques.
The paper tackles the challenge of balancing the benefits of genomic data analysis with privacy and security concerns, proposing visions for secure platforms and a conceptual system model to enable responsible collaboration.
The cost of DNA sequencing has resulted in a surge of genetic data being utilised to improve scientific research, clinical procedures, and healthcare delivery in recent years. Since the human genome can uniquely identify an individual, this characteristic also raises security and privacy concerns. In order to balance the risks and benefits, governance mechanisms including regulatory and ethical controls have been established, which are prone to human errors and create hindrance for collaboration. Over the past decade, technological methods are also catching up that can support critical discoveries responsibly. In this paper, we explore regulations and ethical guidelines and propose our visions of secure/private genomic data storage/processing/sharing platforms. Then, we present some available techniques and a conceptual system model that can support our visions. Finally, we highlight the open issues that need further investigation.