Color single cells on a UMAP dimensional reduction plot according to a feature, i.e. gene expression, PC scores, number of genes detected, etc. As input the user gives the Seurat R-object (.Robj) after the clustering step, and selects the feature of interest.
The resulting UMAP dimension reduction plot colors the single cells according the selected features
available in Seurat objects, such as
percentage of mitochondrial genes (percent.mito), number of unique molecular identifiers (nUMI),
number of genes expressed (nGene) or effect on the first principal components (PCA1 and PCA2).
The plot can be used to visually estimate how the features may effect on the clustering results.
Size of the dots representing the cells can be altered.
For more details, please check the the original tool documentation.