Pancreas (by batch)

Human pancreatic islet scRNA-seq data from 6 datasets across technologies (CEL-seq, CEL-seq2, Smart-seq2, inDrop, Fluidigm C1, and SMARTER-seq).
Raw Scaled
RankNameMean scoreARIARIGraph connectivityGraph connectivityIsolated label F1Isolated label F1NMINMIMemory (GB)Runtime (min)CPU (%)PaperYearLibrary
1Scanorama (hvg/unscaled)0.960.960.961.000.990.950.950.930.933.802.40538.902019v1.7
2scANVI (hvg/unscaled)0.960.950.951.001.000.950.950.920.923.5044.081,108.202021v0.20.0
3Scanorama (hvg/scaled)0.950.950.950.990.990.950.950.920.925.107.08441.202019v1.7
4Combat (hvg/scaled)0.950.950.951.000.990.960.960.920.923.805.77341.802007v1.9.1
5scANVI (full/unscaled)0.950.950.951.001.000.950.940.920.924.90116.772,042.402021v0.20.0
6MNN (hvg/scaled)0.950.940.940.990.990.960.950.910.9180.1013.25479.602018v0.1.9.5
7scVI (hvg/unscaled)0.950.950.950.990.990.950.950.920.912.3045.02565.702018v0.20.0
8scVI (full/unscaled)0.950.940.941.001.000.940.940.910.913.9053.732,636.502018v0.20.0
9Harmony (hvg/unscaled)0.940.940.940.990.990.930.930.920.922.101.63351.602019v0.1.7
10Combat (hvg/unscaled)0.940.940.941.000.990.930.920.910.913.206.25205.202007v1.9.1
11Combat (full/unscaled)0.940.950.950.990.990.890.890.920.9213.803.07561.902007v1.9.1
12BBKNN (hvg/scaled)0.930.920.921.001.000.950.940.860.862.401.30346.602020v1.5.1
13Scanorama (full/scaled)0.930.910.910.990.990.960.950.870.8730.8015.25878.202019v1.7
14BBKNN (hvg/unscaled)0.920.950.951.001.000.850.840.900.902.003.20455.002020v1.5.1
15MNN (hvg/unscaled)0.910.850.851.000.990.930.930.880.8835.805.401,169.802018v0.1.9.5
16SCALEX (hvg)0.910.940.940.990.990.810.800.910.9119.9025.03556.502022v1.0.2
17Harmony (full/unscaled)0.900.910.910.990.990.840.830.870.872.506.30283.602019v0.1.7
18BBKNN (full/unscaled)0.900.910.911.000.990.850.840.860.862.906.40218.102020v1.5.1
19FastMNN feature (hvg/scaled)0.900.930.930.950.940.860.840.880.885.406.58124.302019v1.14.1
20MNN (full/unscaled)0.890.840.840.990.990.890.880.870.87145.5033.131,549.802018v0.1.9.5
21Harmony (hvg/scaled)0.890.910.910.990.980.820.800.870.872.4025.70336.902019v0.1.7
22BBKNN (full/scaled)0.890.830.831.000.990.960.950.780.787.505.05254.402020v1.5.1
23Scanorama gene output (hvg/scaled)0.890.770.770.990.990.950.950.840.845.404.07716.702019v1.7
24Harmony (full/scaled)0.880.830.830.990.980.920.920.810.817.5011.83509.502019v0.1.7
25FastMNN embed (hvg/unscaled)0.870.840.840.950.940.860.840.840.843.003.3394.102019v1.14.1
26SCALEX (full)0.860.920.920.990.990.710.690.860.8629.6058.402,483.402022v1.0.2
27FastMNN embed (full/scaled)0.860.880.880.960.950.810.790.830.8310.4010.1799.102019v1.14.1
28FastMNN embed (hvg/scaled)0.850.790.790.950.940.860.850.830.833.304.3876.202019v1.14.1
29FastMNN embed (full/unscaled)0.850.880.880.960.950.760.740.830.836.507.3084.602019v1.14.1
30FastMNN feature (hvg/unscaled)0.850.790.790.950.940.850.840.830.835.306.27133.402019v1.14.1
31Scanorama gene output (hvg/unscaled)0.850.660.660.990.980.920.920.830.834.709.70413.202019v1.7
32FastMNN feature (full/unscaled)0.840.890.890.960.950.710.690.840.8418.007.25120.302019v1.14.1
33FastMNN feature (full/scaled)0.830.870.870.960.950.720.700.820.8222.5012.38209.902019v1.14.1
34Scanorama gene output (full/scaled)0.820.650.650.980.970.920.920.750.7530.7023.97369.002019v1.7
35Scanorama (full/unscaled)0.800.600.600.990.990.860.850.780.7827.7010.251,249.202019v1.7
36Scanorama gene output (full/unscaled)0.790.610.610.990.990.800.790.760.7627.706.801,478.002019v1.7
37MNN (full/scaled)0.680.520.520.980.980.700.680.540.54501.5054.821,253.602018v0.1.9.5
38Combat (full/scaled)0.630.390.390.940.930.750.730.470.4715.8010.27340.802007v1.9.1
39Liger (hvg/unscaled)0.510.380.380.750.690.640.610.380.383.7037.12101.002019v0.5.0.9000
40Liger (full/unscaled)0.500.370.360.770.710.610.580.360.3613.50174.90100.502019v0.5.0.9000