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@ziw-liu , I have been using 2 UMAP components for plotting and 4 components when I compute correlation with computed features. Does this mean it will change the interpretation of results?
2, 3, and 4 components UMAPs are being used in different places. My intuition is that we should only use 2 components for plotting, and do all the correlations in PC space for better interpretability.
@ziw-liu@Soorya19Pradeep@alishbaimran I agree with Ziwen - use UMAP for plotting/visualization and PCA for computing correlations with engineered features. We should do 3D UMAP renderings in napari, like in zebrahub paper: https://github.com/royerlab/zebrahub-paper-umap-3d. So # of UMAP components can be 2 or 3.
When computing PCA, use the number of components that explain 95% variance of embeddings.
Originally posted by @Soorya19Pradeep in #153 (comment)
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