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Effective quality assessment is an important part of any high-throughput flow cytometry data analysis pipeline, especially when considering the complex designs of the typical flow experiments applied in clinical trials. Technical issues like instrument variation, problematic antibody staining, or reagent lot changes can lead to biases in the extracted cell subpopulation statistics. These biases can manifest themselves in non-obvious ways that can be difficult to detect without leveraging information about the study design or other experimental metadata.
Source text: (Finak et al., 2012) QUAliFiER: an automated pipeline for quality assessment of gated flow cytometry data. BMC Bioinformatics.