Shared resource lab (SRL) strategies for supporting high-dimensional cytometry data analysis

Cytometry A. 2023 Dec;103(12):947-952. doi: 10.1002/cyto.a.24800. Epub 2023 Oct 6.

Abstract

With the increase in the number of parameters that can be detected at the single-cell level using flow and mass cytometry, there has been a paradigm shift when handling and analyzing data sets. Cytometry Shared Resource Laboratories (SRLs) already take on the responsibility of ensuring users have resources and training in experimental design and operation of instruments to promote high-quality data acquisition. However, the role of SRLs downstream, during data handling and analysis, is not as well defined and agreed upon. Best practices dictate a central role for SRLs in this process as they are in a pivotal position to support research in this context, but key considerations about how to effectively fill this role need to be addressed. Two surveys and one workshop at CYTO 2022 in Philadelphia, PA, were performed to gain insight into what strategies SRLs are successfully employing to support high-dimensional data analysis and where SRLs and their users see limitations and long-term challenges in this area. Recommendations for high-dimensional data analysis support provided by SRLs will be offered and discussed.

Keywords: education; flow cytometry; high-dimensional data analysis; shared resource lab.

MeSH terms

  • Data Accuracy
  • Flow Cytometry / methods
  • Laboratories*
  • Research Design*