Frontiers in Immunology (Sep 2023)

Cyclone: an accessible pipeline to analyze, evaluate, and optimize multiparametric cytometry data

  • Ravi K. Patel,
  • Rebecca G. Jaszczak,
  • Kwok Im,
  • Kwok Im,
  • Kwok Im,
  • Nicholas D. Carey,
  • Nicholas D. Carey,
  • Nicholas D. Carey,
  • Tristan Courau,
  • Tristan Courau,
  • Tristan Courau,
  • Tristan Courau,
  • Daniel G. Bunis,
  • Bushra Samad,
  • Lia Avanesyan,
  • Lia Avanesyan,
  • Lia Avanesyan,
  • Lia Avanesyan,
  • Nayvin W. Chew,
  • Nayvin W. Chew,
  • Nayvin W. Chew,
  • Sarah Stenske,
  • Sarah Stenske,
  • Jillian M. Jespersen,
  • Jillian M. Jespersen,
  • Jean Publicover,
  • Jean Publicover,
  • Austin W. Edwards,
  • Mohammad Naser,
  • Arjun A. Rao,
  • Leonard Lupin-Jimenez,
  • Matthew F. Krummel,
  • Matthew F. Krummel,
  • Matthew F. Krummel,
  • Stewart Cooper,
  • Stewart Cooper,
  • Stewart Cooper,
  • Jody L. Baron,
  • Jody L. Baron,
  • Jody L. Baron,
  • Alexis J. Combes,
  • Alexis J. Combes,
  • Alexis J. Combes,
  • Alexis J. Combes,
  • Alexis J. Combes,
  • Gabriela K. Fragiadakis,
  • Gabriela K. Fragiadakis

DOI
https://doi.org/10.3389/fimmu.2023.1167241
Journal volume & issue
Vol. 14

Abstract

Read online

In the past decade, high-dimensional single-cell technologies have revolutionized basic and translational immunology research and are now a key element of the toolbox used by scientists to study the immune system. However, analysis of the data generated by these approaches often requires clustering algorithms and dimensionality reduction representation, which are computationally intense and difficult to evaluate and optimize. Here, we present Cytometry Clustering Optimization and Evaluation (Cyclone), an analysis pipeline integrating dimensionality reduction, clustering, evaluation, and optimization of clustering resolution, and downstream visualization tools facilitating the analysis of a wide range of cytometry data. We benchmarked and validated Cyclone on mass cytometry (CyTOF), full-spectrum fluorescence-based cytometry, and multiplexed immunofluorescence (IF) in a variety of biological contexts, including infectious diseases and cancer. In each instance, Cyclone not only recapitulates gold standard immune cell identification but also enables the unsupervised identification of lymphocytes and mononuclear phagocyte subsets that are associated with distinct biological features. Altogether, the Cyclone pipeline is a versatile and accessible pipeline for performing, optimizing, and evaluating clustering on a variety of cytometry datasets, which will further power immunology research and provide a scaffold for biological discovery.

Keywords