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White S, Quinn J, Enzor J, et al. FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows. Front Immunol. 2021;12:768541doi: 10.3389/fimmu.2021.768541.
White, S., Quinn, J., Enzor, J., Staats, J., Mosier, S. M., Almarode, J., Denny, T. N., Weinhold, K. J., Ferrari, G., & Chan, C. (2021). FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows. Frontiers in immunology, 12768541. https://doi.org/10.3389/fimmu.2021.768541
White, Scott, et al. "FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows." Frontiers in immunology vol. 12 (2021): 768541. doi: https://doi.org/10.3389/fimmu.2021.768541
White S, Quinn J, Enzor J, Staats J, Mosier SM, Almarode J, Denny TN, Weinhold KJ, Ferrari G, Chan C. FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows. Front Immunol. 2021 Nov 05;12:768541. doi: 10.3389/fimmu.2021.768541. eCollection 2021. PMID: 34804056; PMCID: PMC8602902.
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Front Immunol. 2021 Nov 05;12:768541. doi: 10.3389/fimmu.2021.768541. eCollection 2021.

FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows.

Frontiers in immunology

Scott White, John Quinn, Jennifer Enzor, Janet Staats, Sarah M Mosier, James Almarode, Thomas N Denny, Kent J Weinhold, Guido Ferrari, Cliburn Chan

Affiliations

  1. Duke Center for AIDS Research, Duke University, Durham, NC, United States.
  2. Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, United States.
  3. Center for Human Systems Immunology, Duke University Medical Center, Durham, NC, United States.
  4. BD Life Sciences - FlowJo, Ashland, OR, United States.
  5. Duke Immune Profiling Core, Duke University School of Medicine, Durham, NC, United States.
  6. Department of Surgery, Duke University Medical Center, Durham, NC, United States.
  7. Duke Human Vaccine Institute, Durham, NC, United States.

PMID: 34804056 PMCID: PMC8602902 DOI: 10.3389/fimmu.2021.768541

Abstract

An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increasing data complexity, but by and large, still conduct all analysis using traditional applications, predominantly FlowJo. To a large extent, this cuts domain experts off from the rapidly growing library of Single Cell Data Science algorithms available, curtailing the potential contributions of these experts to the validation and interpretation of results. To address this challenge, we developed FlowKit, a Gating-ML 2.0-compliant Python package that can read and write FCS files and FlowJo workspaces. We present examples of the use of FlowKit for constructing reporting and analysis workflows, including round-tripping results to and from FlowJo for joint analysis by both domain and quantitative experts.

Copyright © 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan.

Keywords: FlowJo; GatingML; flow cytometry; python (programming language); single cell data science; software; systems immunology

Conflict of interest statement

Authors JQ and JA were employed by BD Biosciences - FlowJo. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be cons

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