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Table 2 Median F1 of the eight scRNAseq data classifier tools and the four conventional classifiers on the seven datasets (N = 1000)

From: Single-cell classification using graph convolutional networks

Methods

Zhengsorted

Zheng68K

BaronHuman

Muraro

Segerstolpe

BaronMouse

Xin

sigGCN

0.965

0.776

0.977

1

1

0.969

0.995

FC

0.952

0.681

0.938

1

0.968

0.902

0.997

scID

0.66

0.535

0.22

0.578

0

0

1

scPred

0.568

0.105

0.833

0.932

0.8

0.97

0.784

CasTLe

0.834

0.667

0.956

0.967

0.965

0.848

0.997

SingleR

0.678

0.335

0.946

0.984

1

0.898

1

scmapcluster

0.729

0.357

0.9

0.997

0.965

0.88

0.991

scmapcell

0.305

0.198

0.95

0.993

0.977

0.942

0.708

ACTINN

0.892

0.753

1

0.97

1

1

0.997

RF

0.853

0.646

0.956

0.987

0.993

0.984

0.997

SVM-linear

0.868

0.663

0.362

1

0.059

0.238

1

SVM-rbf

0.9

0.671

0.906

1

0.772

0.695

1

KNN

0.795

0.613

0.928

1

0.961

0.889

1