{flowDiv} workflow: reproducible cytometric diversity estimates

QUIROGA M.V.; WANDERLEY B.M.S.; AMADO A.M.; UNREIN F.

Vienna (online)

Conferencia; UseR! 2021 - The R Conference; 2021

The R Foundation for Statistical Computing

Abstract: Flow cytometry is widely used in life sciences, as it records thousands of single-cell data related to their morphological or physiological state within minutes. Hence, each sample has a characteristic cytometric pattern that can be studied through diversity indexes: evenness, alpha- and beta-diversity. Applying this approach to microbial ecology research frequently involves intricate handling of data recorded with different instrumental settings or sample dilutions. The {flowDiv} package overcomes this through data normalization and volume correction steps before estimating cytometric diversity. Here, we share a reproducible {flowDiv} workflow, hoping to help researchers to streamline flow cytometry data processing.Link to package or code repository: https://github.com/bmsw/Supplementary-Code Link to slides: https://mvquiroga.github.io/useR2021_flowDiv Link to Elevator Pitch video: https://youtu.be/bXrJkQk_zwQ