HiChIP Manuscript Code

October 16, 2024 ยท View on GitHub

This repository contains the analysis and plotting scripts for the HiChIP manuscript, designed to process and analyze data from TCGA enhancers and gene interactions.

Table of Contents

Installation

Clone the repository:

git clone https://github.com/NCICCGPO/HiChIP-Manuscript.git
cd HiChIP-Manuscript

Install the necessary dependencies for R and Python scripts. You may need R, Python 3.x, and the following libraries:

  • R packages: ggplot2, dplyr, etc.
  • Python packages: matplotlib, numpy, etc.

For R:

install.packages(c("ggplot2", "dplyr", ...))

For Python:

pip install matplotlib numpy

Usage

The repository contains multiple R and Python scripts, each performing different tasks related to HiChIP analysis. Below are the primary scripts and their usage:

  1. TCGA Enhancer Analysis:

    • 1_TCGA_Enhancers_Gene_Interactions.r: Analysis of enhancer-gene interactions using TCGA data.
    • 2_TCGA_Enhancer_Copy_Number_Regression.r: Performs regression analysis on enhancer copy number data.

    Example:

    Rscript 1_TCGA_Enhancers_Gene_Interactions.r

  2. RNA Modeling:

    • 3_TCGA_RNA_Modeling.r: RNA modeling analysis for TCGA data.
    • 4_TCGA_RNA_Modeling_Analysis.r: Detailed RNA modeling analysis.

    Example:

    Rscript 3_TCGA_RNA_Modeling.r

  3. Visualization:

    • Plot_heatmaps.R: Plots heatmaps for various interaction data.
    • plot_neoloop_dist.py: Python script for plotting neo-loop distributions.

    Example:

    python plot_neoloop_dist.py

For more detailed usage, see each script's comments and documentation.

Code Overview

  • Enhancer Analysis:

    • 1_TCGA_Enhancers_Gene_Interactions.r
    • 2_TCGA_Enhancer_Copy_Number_Regression.r
    • TCGA_King_Enhancer_Interaction_Functions.r

  • RNA Modeling:

    • 3_TCGA_RNA_Modeling.r
    • 4_TCGA_RNA_Modeling_Analysis.r
    • TCGA_King_RNA_modeling_functions.r

  • Visualization:

    • Plot_heatmaps.R
    • plot_neoloop.py
    • Plot_EIS.R

  • Workflow Scripts:

    • HiChIP_decomposition_workflow.R: Main workflow for HiChIP data decomposition.
    • Non_coding_workflow_Final.R: Non-coding region workflow.

Contributing

If you'd like to contribute, please fork the repository and use a feature branch. Pull requests are welcome.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

This project was developed with data from TCGA and contributions from multiple collaborators in the HiChIP community.