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Table 1 Microarray datasets

From: Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data

Dataset

samples

features

class 1(#samples)

class 2(#samples)

1 Wang et al. - Breast cancer [50]

286

22.283

ER+(209)

ER-(77)

2 Verhaak et al. - Leukemia [51]

461

54.675

NPM1 pos.(140)

NPM1 neg.(321)

3 Haferlach et al. - Leukemia [52]

251

54.675

NPM1 pos.(138)

NPM1 neg.(113)

4 Haferlach et al. - Leukemia [52]

77

54.675

AML with t(8;21)(40)

AML with t(15;17)(37)

5 Golub et al. - Leukemia [53]

72

7.129

ALL(47)

AML(25)

6 Chiaretti et al. - Leukemia [54]

22

12.625

CLL stable(8)

CLL progressive(14)

7 Alizadeh et al. - Lymphoma [55]

38

18.432

Activated B-like DLBCL(17)

GC B-like DLBCL(21)

8 Nutt et al. - High-grade glioma [56]

50

12.625

Glioblastoma(28)

Anaplastic oligodendroglioma(22)

9 Alon et al. - Colon cancer [57]

62

2.000

Tumor(42)

Normal(20)

10 Singh et al. - Prostate cancer [58]

102

12.600

Tumor(52)

Normal(50)

  1. Summary of all ten microarray gene expression datasets we used for testing the dimension reduction techniques. Here, we focus on the data by Wang et al., which represents best the results of the whole benchmark. Datasets 2-10 are shortly discussed in the supplement to this work. All datasets were separated into two classes according to two characteristics or the diagnosis of a disease.