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Table 1 Overview of the considered datasets. The third to the eighth column show the numbers of features in the respective feature blocks (clin: clinical covariates, cnv: CNV, mirna: miRNA, mut: DNAseq, met: methylation, rna: mRNA). The last four columns show, in this order, the total number of features (f), the numbers of observations (n), the numbers of observed events (n_e), and the proportions of observed events (r_e)

From: Does combining numerous data types in multi-omics data improve or hinder performance in survival prediction? Insights from a large-scale benchmark study

Dataset

Cancer

clin

cnv

mirna

mut

met

rna

f

n

n_e

r_e

BLCA

Bladder urothelial

5

57,964

825

18,577

382,711

23,081

483,166

382

103

0.27

BRCA

Breast invasive C.

8

57,964

835

17,975

21,919

22,694

121,398

735

72

0.10

COAD

Colon AC.

7

57,964

802

18,538

22,418

22,210

121,942

191

17

0.09

ESCA

Esophageal C.

6

57,964

763

12,628

383,295

25,494

480,153

106

37

0.35

HNSC

Head–neck squamous CC.

11

57,964

793

17,248

376,058

21,520

473,597

443

152

0.34

LGG

Low grade glioma

10

57,964

645

9235

373,499

22,297

463,653

419

77

0.18

LIHC

Liver hepatocellular C.

11

57,964

776

11,821

378,427

20,994

469,996

159

35

0.22

LUAD

Lung AC.

9

57,964

799

18,388

22,486

23,681

123,330

426

101

0.24

LUSC

Lung squamous CC.

9

57,964

895

18,500

21,364

23,524

122,259

418

132

0.32

PAAD

Pancreatic AC.

10

57,964

612

12,392

375,464

22,348

468,793

124

52

0.42

SARC

Sarcoma

11

57,964

778

10,001

378,139

22,842

469,738

126

38

0.30

SKCM

Skin cutaneous M.

9

57,964

1002

18,593

377,193

22,248

477,012

249

62

0.21

STAD

Stomach AC.

7

57,964

787

18,581

22,557

26,027

125,926

295

62

0.21

UCEC

Uterine corpus EC.

11

57,447

866

21,053

22,517

23,978

125,875

405

38

0.09

  1. Abbreviations C. indicates carcinoma; AC., adenocarcinoma; CC., cell carcinoma; M., melanoma; EC., endometrial carcinoma