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"This work suggests an approach to analyze the results obtained in multicolor flow cytometry experiments, for both markers and experimental factors simultaneously. " It is based on an initial multiset PCA model to identify the key variation patterns of cell marker expression, as well as an ASCA model based on the histograms created from these PCA scores. The proposed method estimated the effect size and statistical significance of all the experimental factors and their interactions from a data set from a study of the immune response to prolonged physical activity. The application of a time-u2010-guided sequential clustering scheme to the ASCA scores revealed a stratification of the tested individuals based on their neutrophil activation constants. According to such properties, the proposed ASCA incorporation is an effective and complementary addition to the chemometric techniques used to analyze MFC results. ".
Source link: https://onlinelibrary.wiley.com/doi/10.1002/cem.3402
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