lab319/muti_omics_trs

Muti-Omics_PRS code

Muti_Omics_TRS

Contact:

[email protected]

Citation: Xiaoyu Hou, Baoshan Ma*, Ming Liu, Yuxuan Zhao, Bingjie Chai, Jianqiao Pan, Pengcheng Wang, Di Li, Shuxin Liu*, Fengju Song*. The Transcriptional Risk Scores for Kidney Renal Clear Cell Carcinoma Using XGBoost and Multiple Omics Data.(under review)

This repository contains python implementation of the algorithms proposed in "The Transcriptional Risk Scores for Kidney Renal Clear Cell Carcinoma Using XGBoost and Multiple Omics Data".

The datasets of the program The datasets used during the current study are available from the TCGA website (https://portal.gdc.cancer.gov/)

The describe of the program

Data preprocessing: preprocessed data can be used to test the models, the programs can directly process the data downloaded by TCGA.

model: TRS method utilizing multiple omics data and XGBoost model and a combination model of TRS derived from each omic data