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Table 1 Cell type clustering and batch correction performance on integrating multiple scRNA-seq datasets. The clustering performance is measured by the normalized mutual information (NMI), where NMIcluster=1 implies correct clustering by cell type annotations. (1−NMIbatch)=1 implies no batch effect present after integration. Hyperparameter m is the number of “ghost” cells, and d is the dimension of the reduced gene expression matrix. The bolded entries are the best performance metrics for each scenario. See the “Methods” section for details on NMIcluster and NMIbatch and Additional file 2: Table S1 for additional evaluation metrics

From: One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data

Dataset

ncells

ngenes

m

d

Metric

OCAT

Seurat

Harmony

Scanorama

Human dendritic

576

16,594

20

80

NMIcluster

0.7718

0.7375

0.7653

0.7212

     

1- NMIbatch

0.9999

0.9999

1.0000

0.9999

Mouse atlas

6,954

5,558

45

70

NMIcluster

0.8006

0.6981

0.7625

0.6960

     

1- NMIbatch

0.9999

0.9970

0.9959

0.9905

Human pancreas

14,767

15,558

65

60

NMIcluster

0.7949

0.7947

0.7302

0.7249

     

1- NMIbatch

0.9650

0.9762

0.9600

0.9538

PBMC

15,476

33,694

40

120

NMIcluster

0.7424

0.7932

0.7851

0.7141

     

1- NMIbatch

0.9934

0.9943

0.9944

0.9939

Mouse hematopoietic

4,649

3,467

30

70

NMIcluster

0.5019

0.4606

0.4111

0.5160

     

1- NMIbatch

0.9648

0.9673

0.9734

0.9674