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Gene-network-analysis

This repository has been created to present the work done on computational analysis of fused co-expression networks for the identification of candidate cancer gene biomarkers.

The jupyter notebook Pipeline.ipynb contains the complete pipeline for the construction of the fused co-expression networks and the extraction of relevant gene biomarkers.

The jupyter notebook Knowledge-based evaluation of the results.ipynb contains systematic and statistic evaluation of the extracted genes (here called IC genes).

What can you find in this repository?

This repository contains all data, scripts and results related to the LIHC tumor analysis. In particular, you will find:

How to run the notebook

pip install -r requirements.txt

Execute the jupyter notebook Pipeline.ipynb until the part 'After extraction of communities with Gephi'. Use Gephi in order to extract the relevant communities and save the genes in the folder Extracted with the name 'IC_'+str(tumor)+'.csv'.