Fig. 1
From: GiniClust3: a fast and memory-efficient tool for rare cell type identification
Analysis of mouse brain dataset with more than one million cells. a An overview of the GiniClust3 pipeline. Input single-cell expression matrix is clustered based on features selected by Gini index (GiniIndexClust) and by Fano factor (FanoFactorClust), respectively. The results are then integrated using a cluster-aware, weighted consensus clustering algorithm (ConsensusClust). b UMAP visualization of the gene expression patterns based on Fano-factor (top) and Gini index (bottom) selected features, respectively. Consensus clustering results are indicated by different colors. c The proportion of rare cell cluster in entire population. d Heatmap of cell type mapping of common and rare clusters from scMCA analysis. Bar plot in the top indicates the cell number for each cluster