The top 100 principal components were then used as input to UMAP for generating 2D projections of the data. For subclustering, main clusters 1 – 10 were each individually processed using top 25 principal components in the subset data as input to UMAP dimensionality reduction and Louvain clustering.
Trapnell Lab: Dimensionality reduction by UMAP to visualize physical and genetic interactions