Introduction

Code to study the effect of Hypoxia inducible factor-1A on the metabolic functions of hepatocellular carcinoma.

Computational Framework

This pipeline performs the following tasks:

• Retrieve the data from TCGA using the GDC package
• Data filtering and normalization
• Differential expression analysis using deseq2 package
• Data visualization for the results in the form of a volcano plot using ggplot2
• Data visualization based on the different groups we had using boxplot
• Principal Component Analysis using using plotPCA() from the DESeq2 package
• Survival Analysis using Kaplain Mier and Logrank test.

Installation and Prerequisites

the whole pipeline is developed with the R language

Installation and prerequisites

• Rstudio version 4.1.2 (2021-11-01)

• install the required packages Use the R installation install.package to install the following packages.

• R packages:

  -DESeq2 1.18.0
  -ggplot2 3.5.1
  -tidyr
  -GDC -ggplot2
  -survival 3.5.7
  -cowplot 1.1.3
  -survminer 0.4.9

-Bioconductor annotations for: Human: org.Hs.eg.db

install.package("deseq2")

Download

• download the project as a zip file and then import the zip file as a project in Rstudio
• Use git clone

Usage

Download our RNAseq pipeline. Make sure all dependencies are installed and the right paths are set in the pipeline.

make sure that all the used packages are installed before running the code.

The initial data download step from TCGA can be bypassed by utilizing the pre-existing data file named "Gene_Counts.zip" within the designated "data" folder. This Gene_Counts file can be directly employed for conducting Deseq2_analysis.

Citation

If you use this work, or any of the associated code/materials, in your own research or publication, please cite our paper:

Khedr, M.A., Mohamed, Z., El-Derby, A.M. et al. Development of hepatocellular carcinoma organoid model recapitulating HIF-1A metabolic signature. Clin Exp Med 25, 9 (2025). https://doi.org/10.1007/s10238-024-01521-x