Plotting

To leverage FACSPy’s plotting capabilities, you can use its pl module.

pl.biax	Plot for normal biaxial representation of cytometry data.
pl.fold_change	Plots the asinh fold change.
pl.cluster_frequency	Plots the cluster frequency per cluster as a combined strip-/boxplot.
pl.cluster_abundance	Plots the frequency as a stacked bar chart of a grouping variable per cluster.
pl.marker_density	Histogram Plot of marker expression.
pl.mfi	Plots the median fluorescence intensity (mfi) values as calculated by fp.tl.mfi as a combined strip-/boxplot.
pl.fop	Plots the frequency of parent (fop) values as calculated by fp.tl.fop as a combined strip-/boxplot.
pl.sample_correlation	Plot for sample correlation.
pl.sample_distance	Plot to display sample to sample distance as a heatmap.
pl.pca_samplewise	Plot for visualizing sample-wise dimensionality reduction (PCA) as a scatter plot.
pl.mds_samplewise	Plot for visualizing sample-wise dimensionality reduction (MDS).
pl.tsne_samplewise	Plot for visualizing sample-wise dimensionality reduction (TSNE).
pl.umap_samplewise	Plot for visualizing sample-wise dimensionality reduction (UMAP).
pl.cofactor_distribution	Plots the cofactor distribution of specific channels.
pl.transformation_plot	Transformation plot.
pl.gating_strategy
pl.cell_counts	Plots the cell counts of a specific population.
pl.gate_frequency	Plots the gate frequency in comparison to a defined gate.
pl.expression_heatmap	Plot for expression heatmap.
pl.cluster_heatmap	Plots a heatmap where every column corresponds to one cluster and the rows display the marker expression.
pl.cluster_mfi	Plots the median fluorescence intensity (mfi) values as calculated by fp.tl.mfi as a combined strip-/boxplot for the indicated clustering.
pl.cluster_fop	Plots the frequency of parent (fop) values as calculated by fp.tl.fop as a combined strip-/boxplot for the indicated clustering.
pl.marker_correlation	Plot for marker correlation heatmap.
pl.metadata	Plots the frequency of the metadata columns.
pl.umap	Plots the UMAP embedding.
pl.pca	Plots the PCA embedding.
pl.diffmap	Plots the diffusion embedding.
pl.tsne	Plots the TSNE embedding.