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Genome Med. 2014 Sep 17;6(9):71. doi: 10.1186/s13073-014-0071-9. eCollection 2014.

NGS-Logistics: federated analysis of NGS sequence variants across multiple locations.

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KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Kasteelpark Arenberg 10, Box 2446, 3001 Leuven, Belgium ; iMinds Medical IT Department, Kasteelpark Arenberg 10, Box 2446, 3001 Leuven, Belgium.
KU Leuven, Center of Human Genetics Gasthuisberg, O&N I Herestraat 49, Box 602, 3000 Leuven, Belgium.


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 identifiers. This approach minimizes the impact on data confidentiality while enabling powerful data analysis by gaining access to important rare samples. Our methodology is implemented in an open source tool called NGS-Logistics, freely available at

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