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SWGTS-a platform for stream-based host DNA depletion.

Philipp Spohr1,2, Max Ried1,2, Laura Kühle1,2

  • 1Algorithmic Bioinformatics, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany.

Bioinformatics (Oxford, England)
|May 24, 2024
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Summary

We developed SWGTS, a stream-based tool for removing human DNA sequences from microbial data during transfer. This enhances data privacy and complies with regulations like GDPR by limiting exposure of genetic information.

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Area of Science:

  • Bioinformatics
  • Genomic Data Analysis
  • Computational Biology

Background:

  • Clinical microbial sequencing generates data often contaminated with human DNA.
  • Current human read removal methods require full data retrieval, posing privacy risks and GDPR compliance challenges.
  • Stream-based host depletion during data transfer is a preferable alternative for sensitive genetic data.

Purpose of the Study:

  • To present SWGTS, a client-server application for stream-based host depletion of sequencing reads.
  • To ensure privacy and regulatory compliance by processing genetic data in transit.
  • To mitigate re-identification risks associated with sharing clinical sequencing data.

Main Methods:

  • SWGTS employs a client-server architecture with a limited-size buffer to control memory usage of human genetic data.
  • Data transfer rates are throttled to match the server's background host depletion speed.
  • The application utilizes Docker, Redis, and Traefik, requiring minimal RAM (<8 GB).

Main Results:

  • SWGTS achieves high filtering accuracy for human read removal.
  • Demonstrated data transfer rates up to 1.65 megabases per second in a conservative configuration.
  • Successfully mitigates re-identification risks by limiting the number of detectable SNPs.

Conclusions:

  • SWGTS offers an efficient and secure method for handling contaminated microbial sequencing data.
  • The stream-based approach enhances data privacy and regulatory compliance.
  • SWGTS is readily available on GitHub with reproducible benchmarks.