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Metabolomics and Drug Response Analysis in Cancer Cell Lines

This R project analyzes the relationship between metabolomics data and drug responses in cancer cell lines using various datasets, including CCLE (Cancer Cell Line Encyclopedia) and CTRP (Cancer Therapeutics Response Portal).

Features

  • Data acquisition and preprocessing from multiple sources
  • Correlation analysis between metabolite concentrations and drug responses
  • Hypergeometric enrichment analysis for protein targets and metabolic pathways
  • Visualization of results using various plot types (heatmaps, volcano plots, etc.)

Prerequisites

Before running this project, ensure you have R installed (version 4.0.0 or higher) along with the following R packages:

install.packages(c("tidyverse", "data.table", "readxl", "RCurl", "heatmaply", "pals", "scales", "hrbrthemes", "viridis", "forcats", "EnhancedVolcano", "ComplexHeatmap", "ggrepel", "ggpubr", "grid", "gridExtra", "splitstackshape", "fuzzyjoin", "plyr"))

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("RCppEigen")

Project Structure

The project consists of a single R script (altogether.R) that performs the following main steps:

  1. Data acquisition and preprocessing
  2. Correlation analysis
  3. Hypergeometric enrichment analysis
  4. Visualization of results

Usage

  1. Clone this repository:

    git clone https://github.com/yourusername/metabolomics-drug-response-analysis.git
cd metabolomics-drug-response-analysis

  2. Open the altogether.R script in your R environment (e.g., RStudio).

  3. Run the script section by section, following the comments that describe each step.

Main Analyses

1. Data Acquisition and Preprocessing

  • Downloads and processes CCLE metabolomics data
  • Acquires and processes CTRP drug response data
  • Merges datasets and performs initial data cleaning

2. Correlation Analysis

  • Calculates correlations between metabolite concentrations and drug responses
  • Filters for significant correlations

3. Hypergeometric Enrichment Analysis

  • Performs enrichment analysis for protein targets and metabolic pathways
  • Identifies significantly enriched targets and pathways

4. Visualization

  • Generates various plots, including:
    • Volcano plots by TCGA cancer type
    • Heatmaps of correlations between metabolites and drugs
    • Scatter plots of drug responses vs. metabolite concentrations

Output

The script generates several output files, including:

  • Processed data files (saved as .RData files in the Data/ directory)
  • Visualization plots (saved as PDF files in the Plots/ directory)

Customization

You can customize the analysis by modifying parameters such as correlation thresholds, p-value cutoffs, and visualization settings within the script.

Contributing

Contributions to improve the analysis pipeline are welcome. Please fork the repository and submit a pull request with your changes.

License

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

Acknowledgments

  • This project uses data from the Cancer Cell Line Encyclopedia (CCLE) and the Cancer Therapeutics Response Portal (CTRP).
  • Various R packages and libraries are used for data manipulation and visualization. Please cite them appropriately in your research.