Mouse myeloid lineage differentiation

Myeloid lineage differentiation from mouse blood. Sequenced by SMARTseq in 2016 by Olsson et al. 660 cells x 112815 features with 4 cell type labels
Raw Scaled
RankNameMean scoreDistance correlation (spectral)Distance correlation (spectral)Distance correlationDistance correlationco-KNN AUCco-KNN AUCco-KNN sizeco-KNN sizecontinuitycontinuitydensity preservationdensity preservationglobal propertyglobal propertylocal continuity meta criterionlocal continuity meta criterionlocal propertylocal propertytrustworthinesstrustworthinessMemory (GB)Runtime (min)CPU (%)PaperYearLibrary
1densMAP (logCP10k)0.720.141.850.430.640.710.430.550.530.980.960.851.150.73-0.040.510.530.530.190.960.930.472.0237.302021v0.5.3
2UMAP (logCP10k)0.610.162.060.420.630.690.380.510.480.980.950.080.130.71-0.140.460.480.520.180.960.920.470.9777.802018v0.5.3
3NeuralEE (CPU) (Default)0.560.081.330.400.600.700.400.520.500.980.960.230.340.72-0.100.480.500.520.180.960.912.100.87210.602020v0.1.6
4PyMDE Preserve Neighbors (logCP10k)0.560.131.730.380.570.680.370.490.460.970.950.070.120.71-0.150.440.460.510.160.960.920.853.501,243.702021v0.1.18
5t-Distributed Stochastic Neighbor Embedding (t-SNE) (logCP10k)0.550.081.320.270.400.680.350.540.520.980.950.400.550.69-0.200.490.520.510.160.970.930.5419.30186.102008v0.1
6densMAP PCA (logCP10k)0.550.061.090.220.340.650.300.520.500.980.950.781.050.66-0.310.480.500.500.130.970.930.570.95361.202021v0.5.3
7densMAP PCA (logCP10k, 1kHVG)0.540.020.740.380.560.690.390.470.440.970.940.680.920.72-0.090.420.440.490.120.950.900.430.99105.202021v0.5.3
8UMAP PCA (logCP10k)0.500.081.320.330.490.670.340.490.470.970.940.090.140.69-0.200.440.470.510.160.960.920.572.02423.002018v0.5.3
9PHATE (default)0.490.091.430.410.620.670.340.440.410.970.94-0.06-0.050.70-0.190.400.410.480.100.950.910.552.95132.302019v1.0.10
10PHATE (logCP10k)0.490.081.260.400.590.660.320.440.410.970.930.130.200.69-0.230.390.410.470.100.950.910.501.37277.902019v1.0.10
11NeuralEE (CPU) (logCP10k, 1kHVG)0.490.030.850.310.460.690.380.450.420.960.910.400.560.72-0.110.400.420.460.070.950.900.581.42234.402020v0.1.6
12densMAP (logCP10k, 1kHVG)0.470.030.800.270.400.630.270.450.420.960.910.640.870.66-0.350.400.420.430.030.940.890.410.8177.602021v0.5.3
13Principle Component Analysis (PCA) (logCP10k)0.450.101.450.220.340.620.250.410.390.960.920.180.270.65-0.380.370.380.460.070.900.790.411.1546.301901v1.1.3
14PyMDE Preserve Neighbors (logCP10k, 1kHVG)0.450.040.920.400.590.680.360.470.450.970.93-0.05-0.040.71-0.140.420.440.440.040.950.900.600.67214.902021v0.1.18
15t-Distributed Stochastic Neighbor Embedding (t-SNE) (logCP10k, 1kHVG)0.430.020.720.280.420.670.340.490.470.970.940.130.200.69-0.210.450.470.470.080.960.910.401.63338.202008v0.1
16PHATE (gamma=0)0.430.081.250.380.570.680.360.420.390.970.93-0.33-0.410.71-0.150.370.390.460.080.950.900.550.55386.102019v1.0.10
17Principle Component Analysis (PCA) (logCP10k, 1kHVG)0.43-0.030.200.210.320.680.360.460.440.970.920.560.770.70-0.160.420.440.480.110.950.890.401.2529.101901v1.1.3
18PHATE (logCP10k, 1kHVG)0.420.000.550.300.450.670.330.430.410.970.930.250.350.69-0.210.390.400.470.080.950.900.400.89245.202019v1.0.10
19UMAP (logCP10k, 1kHVG)0.360.020.740.260.390.640.270.450.420.960.91-0.09-0.090.66-0.340.400.420.430.020.940.880.430.9793.802018v0.5.3
20UMAP PCA (logCP10k, 1kHVG)0.350.010.610.210.320.650.300.450.420.970.93-0.16-0.180.67-0.290.400.420.490.120.950.900.421.0096.802018v0.5.3
21PyMDE Preserve Distances (logCP10k)0.320.071.180.370.550.580.150.220.180.830.630.460.640.62-0.480.170.180.29-0.220.720.420.934.22542.202021v0.1.18
22PyMDE Preserve Distances (logCP10k, 1kHVG)0.30-0.050.010.230.340.660.310.320.280.800.570.650.880.70-0.190.270.280.35-0.110.830.640.791.28188.302021v0.1.18