scDSSC: Deep Sparse Subspace Clustering for scRNA-seq Data
Fig 6
scDSSC is capable on simulation datasets.
Plot A shows the clustering performance of scDSSC on 12 simulated datasets. The six datasets in the left panel are generated when the dropout rate is set to 0.25, and the six datasets in the right panel are generated when the dropout rate is set to 0.05. Plot B shows the cell visualization results for one of the datasets with five cell types, corresponding to a dropout rate of 0.25. Plot C shows the differential expression analysis for the dataset used in Plot B. The meanings represented by the rows and columns, as well as the meanings represented by the light and dark colors, are consistent with the results of the differential expression analysis described above.