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Table 2 The 25 most relevant genes and the last 3 out of the total number of 54613 according to the proposed KPCA-IG method

From: Improvement of variables interpretability in kernel PCA

Genes

Score

Standard deviation

Symbol

1555797_a_at

0.427972

0.12993

ARPC5

237350_at

0.426140

0.11331

TTC36

1559573_at

0.424048

0.11844

LINC01093

230478_at

0.420690

0.12039

OIT3

203213_at

0.417682

0.11453

CDK1

205019_s_at

0.417597

0.11383

VIPR1

1559065_a_at

0.417234

0.12463

CLEC4G

205984_at

0.417234

0.12607

CRHBP

220114_s_at

0.416410

0.12014

STAB2

202604_x_at

0.416228

0.12273

ADAM10

220496_at

0.415608

0.12558

CLEC1B

205866_at

0.414893

0.11862

FCN3

214895_s_at

0.414887

0.13144

ADAM10

240963_x_at

0.413698

0.12648

PLXDC1

234304_s_at

0.413574

0.13119

IPO11

222077_s_at

0.412939

0.11637

RACGAP1

223341_s_at

0.411044

0.13771

SCOC

214710_s_at

0.410616

0.11262

CCNB1

218009_s_at

0.410610

0.11377

PRC1

219918_s_at

0.410460

0.11532

ASPM

226524_at

0.410119

0.13299

C3orf38

201890_at

0.410097

0.11593

RRM2

207804_s_at

0.409962

0.12230

FCN2

210481_s_at

0.409839

0.12106

CLEC4M

209470_s_at

0.409759

0.12423

GPM6A

...

...

  

229461_x_at

0.0520878

0.088739

NEGR1

230538_at

0.0520119

0.134812

SHC4

206145_at

0.0507935

0.098227

RHAG

  1. The original scores and their standard deviations have been multiplied by \(10^3\) for a better visualization