Multi-omic and survival datasets used for "DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data"

We obtained the 32 cancer multi-omic datasets from NCBI using TCGA portal (https://tcgadata.nci.nih.gov/tcga/). We used the package TCGA-Assembler (versions 2.0.5) and wrote custom scripts
to download RNA-Seq (UNC IlluminaHiSeq RNASeqV2), miRNA Sequencing (BCGSC IlluminaHiSeq,
Level 3), and DNA methylation (JHU-USC HumanMethylation450) data from the TCGA website on
November 4-14th, 2017. We also obtained the survival information from the portal:
https://portal.gdc.cancer.gov/. We used the same preprocessing steps as detailed in our previous study.
We first downloaded RNA-Seq, miRNA-Seq and methylation data using the functions
DownloadRNASeqData, DownloadmiRNASeqData, and DownloadMethylationData from TCGAAssembler, respectively. Then, we processed the data with the functions ProcessRNASeqData,
ProcessmiRNASeqData, and ProcessMethylation450Data. In addition, we processed the methylation data
with the function CalculateSingleValueMethylationData. Finally, for each omic data type, we created a
gene-by-sample data matrix in the Tabular Separated Value (TSV) format using a custom script.