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Table 3 Classes of carcinomas used for random forest prediction of cancer types

From: Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB)

Class name

TCGA cohorts

Sample size

Total

Training set

Test set

Adrenal gland

Adrenocortical carcinoma (ACC)

271

179

92

Pheochromocytoma and paraganglioma (PCPG)

Bladder

Urothelial carcinoma (BLCA)

411

272

139

Brain

Lower grade glioma (LGG)

515

340

175

Breast

Breast invasive carcinoma (BRCA)

1077

711

366

Gastrointestinal

Esophageal carcinoma (ESCA)

1237

817

420

Stomach adenocarcinoma (STAD)

Colon adenocarcinoma (COAD)

Rectum adenocarcinoma (READ)

Cholangiocarcinoma (CHOL)

Head & Neck

Head and neck squamous cell carcinoma (HNSC)

590

390

200

Uveal melanoma (UVM)

Hematologic

Acute myeloid leukemia (LAML)

321

212

109

Diffuse large B-cell lymphoma (DLBC)

Thymoma (THYM)

Kidney

Kidney Chromophobe (KICH)

738

488

250

Renal clear cell carcinoma (KIRC)

Renal papillary cell carcinoma (KIRP)

Liver

Hepatocellular carcinoma (LIHC)

321

212

109

Ovary

Ovarian serous cystadenocatcinoma (OV)

437

289

148

Pancreas

Pancreatic adenocarcinoma (PAAD)

184

122

62

Prostate

Prostate adenocarcinoma (PRAD)

498

329

169

Skin

Cutaneous melanoma (SKCM)

104

69

35

Testis

Testicular germ cell tumors (TGCT)

150

99

51

Thoracic

Lung adenocarcinoma (LUAD)

1143

755

388

Lung squamous cell carcinoma (LUSC)

Mesothelioma (MESO)

Thyroid

Thyroid carcinoma (THCA)

496

327

169

Uterus

Uterine carcinosarcoma (UCS)

598

395

203

Uterine corpus endometrial carcinoma (UCEC)