Collaborative analysis of genomic data: vision and challenges

TL;DR

This paper discusses the challenges and solutions for secure, private, and collaborative analysis of genomic data, emphasizing regulatory, ethical, and technological aspects to enable responsible scientific and clinical use.

Contribution

It proposes a vision for secure genomic data platforms, reviews existing techniques, and presents a conceptual system model to address privacy and collaboration challenges.

Findings

Identification of key privacy and security challenges

Proposed a conceptual framework for secure data sharing

Highlighted open issues for future research

Abstract

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.