Fig. 3
From: scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data
Benchmarking results on real scRNA-seq datasets. Clustering performances of scDeepCluster, scDSC, scDEC, scDHA, SC3, scGAE, scDCC, scAL, Itclust, scSemiAE and scSemiAAE, measured by ACC, NMI and ARI. The first six ones are unsupervised methods, and the remaining ones are semi-supervised clustering algorithms. A Comparison with semi-supervised clustering approaches on three datasets with the top 2000 highly scattered genes. B The results of unsupervised clustering algorithms. C scSemiAAE uses different proportions of labels on seven real datasets, measured by NMI