flowCut: An R package for automated removal of outlier events and flagging of files based on time versus fluorescence analysis

Cytometry A. 2023 Jan;103(1):71-81. doi: 10.1002/cyto.a.24670. Epub 2022 Jul 23.


Technical artifacts such as clogging that occur during the data acquisition process of flow cytometry data can cause spurious events and fluorescence intensity shifting that impact the quality of the data and its analysis results. These events should be identified and potentially removed before being passed to the next stage of analysis. flowCut, an R package, automatically detects anomaly events in flow cytometry experiments and flags files for potential review. Its results are on par with manual analysis and it outperforms existing automated approaches.

Keywords: anomaly detection; bioinformatics; data acquisition; data cleaning; flow cytometry; outlier detection; quality checking.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • Flow Cytometry* / methods