Datasets used for Multi-omics integration using Deep Learning and other state-of-the-art regression models

This repository link contains the LIHC files that were downloaded using TCGA Assembler 2 and used in the publication for benchmarking DL and other state-of-the-art regression models.

The contents are as follows.

Gene level CNA , filename= "LIHC__genome_wide_snp_6__GeneLevelCNA.txt"

DNA Methylation data around 1500 bp around TSS (450K) , filename= "LIHC_Methylation450__SingleValue__TSS1500__Both.txt"

RNASeq  data, filename= "LIHC_RNASeq__illuminahiseq_rnaseqv2__GeneExp.txt"

本仓库链接收录了通过TCGA Assembler 2下载的LIHC数据集文件，相关文件已用于一篇发表论文中，用于基准测试深度学习（Deep Learning, DL）及其他前沿回归模型。

数据集内容如下：

基因水平拷贝数变异（Copy Number Alteration, CNA）数据，文件名为"LIHC__genome_wide_snp_6__GeneLevelCNA.txt"

转录起始位点（Transcription Start Site, TSS）上下游1500bp区域的DNA甲基化（DNA Methylation）数据（基于450K芯片），文件名为"LIHC_Methylation450__SingleValue__TSS1500__Both.txt"

RNA测序（RNA Sequencing, RNASeq）数据，文件名为"LIHC_RNASeq__illuminahiseq_rnaseqv2__GeneExp.txt"