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. Author manuscript; available in PMC: 2022 Aug 16.
Published in final edited form as: Cell Immunol. 2022 Jun 20;378:104572. doi: 10.1016/j.cellimm.2022.104572

Fig. 6. PCA plots for NoTF and TF clustering.

Fig. 6.

The three MAIT cell functions (IFN-γ, TNF-α, and IL-17A production) were analyzed using the FCOM deconvolution tool. FCOM data of the 7 possible combinations were used to perform an unsupervised PCA analysis. Data from NoTF (91 data points) and TF (49 data points) were processed separately. Unit variance scaling was applied to rows; SVD with imputation was used to calculate principal components. X and Y axis show principal component 1 and principal component 2. Prediction ellipses are such that with a probability of 0.95, a new observation from the same group will fall inside the ellipse. (A) PCA and (B) Heatmap. Rows are centered; unit variance scaling was applied to rows. Imputation was used for missing value estimation. Both rows and columns are clustered using correlation distance and average linkage. PCA and heatmap were generated using absolute MAIT cell numbers per microliter of peripheral blood.