Thank you for the insightful answer!
While took your notes and tried to look back any of my previous saved documents, I could not find the version of the Seurat, however I did find this which confirmed your thoughts here:
Run UMAP
seurat_integrated <- RunUMAP(seurat_integrated,
-
dims = 1:40, -
reduction = "pca")
Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session
08:44:03 UMAP embedding parameters a = 0.9922 b = 1.112
08:44:03 Read 29629 rows and found 40 numeric columns
08:44:03 Using Annoy for neighbor search, n_neighbors = 30
08:44:03 Building Annoy index with metric = cosine, n_trees = 50
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08:44:10 Writing NN index file to temp file /var/folders/hr/szgyxy3d5l5ffhm8yj89fqs80000gn/T//Rtmpy6W1ys/file2e7c4a44e5c8
08:44:10 Searching Annoy index using 1 thread, search_k = 3000
08:44:21 Annoy recall = 100%
08:44:22 Commencing smooth kNN distance calibration using 1 thread
08:44:25 Initializing from normalized Laplacian + noise
08:44:27 Commencing optimization for 200 epochs, with 1343698 positive edges
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08:44:43 Optimization finished