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A modern and flexible framework for flow cytometry data in R

flowplyr is a reimagined foundation for working with flow cytometry data in R — designed for modern data science workflows.

It aims to make flow cytometry data accessible, composable, and fully compatible with the tidyverse, functional programming, and other R ecosystems, without forcing any particular paradigm.

✨ Key goals

  • Modern infrastructure – foregoes the use of S4 OOP to provide a simple, transparent data structure.
  • Functional and flexibleflowplyr makes flow data accessible, so you can purrr, dplyr, data.table, or base R as you would any type of data.
  • Interoperable design – easily integrate your flow data analysis with your normal choice of downstream tools for visualization, modeling, saving, and reporting.
  • Unified data representation – handles all fcs-file slots (i.e. expression data and metadata)

📦 Installation

NB! flowplyr is under heavy development and subject to sweeping, rolling changes

You can install the development version of flowplyr from GitHub with:

# install.packages("pak")
pak::pak("hugoakerstrand/flowplyr")

Example

TBD