Frontiers in Immunology (Nov 2021)

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

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

DOI
https://doi.org/10.3389/fimmu.2021.768541
Journal volume & issue
Vol. 12

Abstract

Read online

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.

Keywords