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As many personal genomes are being sequenced, collaborative analysis of those genomes has become essential. However, analysis of personal genomic data raises important privacy and confidentiality issues. We propose a methodology for federated analysis of sequence variants from personal genomes. Specific base-pair positions and/or regions are queried for samples to which the user has access but also for the whole population. The statistics results do not breach data confidentiality but allow further exploration of the data; researchers can negotiate access to relevant samples through pseudonymous identifier. This approach minimizes the impact on data confidentiality while enabling powerful data analysis by gaining access to important rare samples.

Genomics data sharing

The reusability of biological data makes researchers eager to access each other’s data, but creates the additional challenge of providing this access at a sufficiently detailed level.

Our ultimate goal is to provide a way for biomedical researchers to ask high-level questions, such as "what is the frequency of appearance of a single mutation across the large population" or "how many patients with disease D have a mutation in gene G?" transparently.


NGS-Logistics is an open source project. Whole project devided into three solutions: Interface, Access Control List and Query Manager. Source code of each one of these solutions is available in the GitHub.

GitHub repositore