Reproducible and programmatic analysis of flow cytometry experiments with the cytoverse**
Author(s): Arpan Neupane,Mike Jiang,Malisa Smith,Greg Finak,Andrew McDavid
Affiliation(s): Ozette technologies
Social media: https://twitter.com/EquivMeasures
Multi-dimensional flow cytometry remains the gold standard for assessing the presence and abundance of cellular subpopulations in basic science and clinical and translational studies. There is increasing recognition of the importance of replacing ad-hoc GUI tools with automated and programmable workflows. For several years, Bioconductor has hosted the cytoverse: a set of interoperable packages, including flowCore, flowWorkspace, opencyto, ggcyto, cytoqc and others, which all facilitate programmatic flow cytometry analysis in R. Here we provide an overview of these packages in the context of re-analyzing a publicly available data set. At the end of the workshop, attendees will be able to i) import flow cytometry data, ii) understand the difference between uncompensated, compensated, and transformed data, iii) identify and generate important plots to assess data quality, iv) identify subpopulations by manually or semi-automated gating of markers, v) generate plots summarizing the expression of markers and abundance of various subpopulations.