Safeguarding Privacy in Genome Research: A Comprehensive Framework for Authors.

Area of Science:

• Genomics
• Bioinformatics
• Data Privacy

Background:

• Genomic research relies on data sharing for collaboration and discovery.
• Protecting individual genetic privacy is crucial alongside data sharing.
• Re-identification risks, like membership inference attacks (MIA), pose challenges.

Purpose of the Study:

• To present a bidirectional framework for evaluating privacy risks in shared genomic data.
• To assess risks associated with summary statistics and research datasets.
• To ensure compliance with policies like the National Institutes of Health (NIH) genomic data sharing policy.

Main Methods:

• A structured workflow involving a researcher questionnaire on data sharing and privacy measures.
• Calculation of re-identification risk based on self-reported practices.
• Comparison of practices against the NIH genomic data sharing policy.

Main Results:

• The framework identifies vulnerabilities in privacy protection measures.
• It guides researchers in enhancing privacy before publication.
• Case studies demonstrate the framework's application in published genomic research.

Conclusions:

• Bidirectional frameworks are essential for trustworthy open science and genomic data sharing.
• Proactive privacy risk assessment supports secure data sharing practices.
• The framework aids in balancing data accessibility with individual privacy protection.