Functional genomics data: privacy risk assessment and technological mitigation.

Area of Science:

• Genomics
• Bioinformatics
• Data Privacy

Background:

• Next-generation sequencing (NGS) has dramatically increased functional genomics data generation.
• Broad data sharing is crucial for scientific progress but raises significant privacy concerns.
• Existing privacy challenges are similar to those in genetic variant data sharing.

Purpose of the Study:

• To review unique privacy challenges in functional genomics data.
• To identify risks associated with information leakage during data processing.
• To present solutions for mitigating privacy risks in functional genomics data.

Main Methods:

• Review of existing literature on data privacy in genomics.
• Analysis of information leakage points in functional genomics data pipelines.
• Exploration of privacy-preserving techniques for data summarization.

Main Results:

• Functional genomics data present unique privacy risks beyond genetic variant data.
• Cryptic information leakage can occur from raw reads to derived data like gene expression.
• Potential solutions exist to balance data utility with privacy protection.

Conclusions:

• Addressing privacy challenges in functional genomics is essential for continued research.
• Implementing privacy-preserving methods allows for broader data dissemination and analysis.
• Balancing data sharing and privacy is achievable through careful methodology.