Publication | Open Access
<scp>flowCut:</scp> An R package for automated removal of outlier events and flagging of files based on time versus fluorescence analysis
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Citations
7
References
2022
Year
Anomaly DetectionEngineeringPathologyDetection TechniqueR PackageData ScienceData MiningAnomaly EventsOutlier DetectionOmicsBiomedical AnalysisComputer ScienceCytometryOutlier EventsComputational BiologyTechnical ArtifactsSystems BiologyMedicineAutomated RemovalCytopathology
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.
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