Question about umap using different numbers of pca components as initialization

Question

[Zack]

I am new to the scRNA-seq field and I have been doing some experiments of visualization of UMAP using different numbers of PCA components for initialization. The process involves projecting scRNA-seq data (count matrix) onto various numbers of PCA components, followed by non-linear dimension reduction using UMAP. It seems that the UMAP results are exactly the same across different initializations, regardless of the number of PCA components used. Are there any theoretical reasons for this? I am using Dynamo and their function dyn.tl.reduceDimension(adata, n_pca_components=30) for the experiments.