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Table 4 TCGA progression-free interval (PFI) tasks

From: Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data

TCGA PFI tasks   
ProjectDiseaseLabelLabel typeGroupSamples
CESCcervical squamous cell carcinomaPFIsurvivaltrain304
COADcolon adenocarcinomaPFIsurvivaltrain455
ESCAesophageal carcinomaPFIsurvivaltrain184
KIRPkidney papillary cell carcinomaPFIsurvivaltrain288
LUADlung adenocarcinomaPFIsurvivaltrain507
OVovarian cancerPFIsurvivaltrain420
PAADpancreatic adenocarcinomaPFIsurvivaltrain178
SARCsarcomaPFIsurvivaltrain259
STADstomach adenocarcinomaPFIsurvivaltrain411
UCECuterine corpus endometrial carcinomaPFIsurvivaltrain540
HNSChead-neck squamous cell carcinomaPFIsurvivalvalidate501
BLCAbladder urothelial carcinomaPFIsurvivaltest408
LUSClung squamous cell carcinomaPFIsurvivaltest496
  1. The 13 progression-free surivival tasks derived from TCGA used to train supervised models and validate the unsupervised embeddings. The project names correspond to those in Fig. 2