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Use FlowRepository to share your clinical data upon study publication.

Josef Spidlen1, Ryan R Brinkman1,2

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Open data sharing, including flow cytometry data, is crucial for scientific validation and collaboration. De-identified clinical data should routinely accompany cytometry findings to enhance research reproducibility.

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data availabilitydata repositorydata sharingde-identificationprivacyreproducible research

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Area of Science:

  • Biomedical research
  • Clinical cytometry
  • Data science

Background:

  • Scientific rigor demands open access to published results and underlying data for validation.
  • Data sharing fosters collaboration, improves data quality, and minimizes redundant efforts.
  • Existing repositories support microarray, proteomics, and sequencing data, demonstrating the value of data accessibility.

Purpose of the Study:

  • To advocate for routine sharing of de-identified clinical data alongside cytometry-based findings.
  • To highlight the benefits of data sharing for independent validation and reproducibility in clinical cytometry.
  • To address the simultaneous requirements of data sharing and patient privacy in clinical studies.

Main Methods:

  • Discussing methods for de-identifying clinical data to comply with privacy regulations.
  • Highlighting the role of data repositories like FlowRepository for deposition of flow cytometry data.
  • Examining successful data sharing practices in other scientific fields (microarray, proteomics, sequencing).

Main Results:

  • Flow cytometry data sharing is already practiced by authors through platforms like FlowRepository.
  • Successful data sharing models exist in other scientific domains, providing a precedent for clinical data.
  • Methods exist to balance data sharing needs with stringent patient privacy requirements.

Conclusions:

  • Routine sharing of de-identified clinical data is essential for advancing clinical cytometry research.
  • Adopting open data practices will enhance the reliability and impact of cytometry-based findings.
  • The scientific community should embrace data sharing to foster reproducibility and accelerate discovery.