Skip to main content

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.