Table 1 scRNA-seq clustering methods for number of cell type estimation evaluated in this study
Methods | Platform | Clustering type | Category | Ref. | Version |
|---|---|---|---|---|---|
Monocle3 | R | Leiden clustering | Community detection | [22] | 0.2.3.0 |
scLCA | R | Spectral clustering | Intra- and inter-cluster similarity | [9] | 0.0.0.9 |
scCCESS-SIMLR | R | Ensemble of SIMLR | Stability metric | [33] | 0.0.1 |
ACTIONet | R/C++ | Leiden clustering | Community detection | [19] | 2.0.18 |
Seurat | R | Louvain clustering | Community detection | [23] | 4.0.1 |
scCCESS-Kmeans | R | Ensemble of K-means | Stability metric | [33] | 0.0.1 |
CIDR | R | Hierarchical clustering | Intra- and inter-cluster similarity | [11] | 0.1.5 |
SC3 | R | Hierarchical clustering | Eigenvector-based metrics | [27] | 1.18.0 |
SIMLR | R | Spectral clustering | Eigenvector-based metrics | [25] | 1.18.0 |
RaceID | R/C++ | K-means | Intra- and inter-cluster similarity | [14] | 0.2.3 |
SINCERA | R | Hierarchical clustering | Intra- and inter-cluster similarity | [16] | 0.99.0 |
Spectrum | R | Spectral clustering | Eigenvector-based metrics | [26] | 1.1 |
densityCut | R | Hierarchical clustering | Stability metric | [32] | 0.0.1 |
SHARP | R | Meta-clustering | Intra- and inter-cluster similarity | [13] | 1.1.0 |