Regulated Cell Death Playground

Collection of analysis scripts and notebooks related to regulated cell death

The analyses and results can be viewed at https://bioinfodlsu.com/regulated-cell-death-playground/

🧪 Reproducing our results

Operating system: Linux, Windows, or macOS

A. Cloning our repository

1. Clone this repository by running:

   git clone https://github.com/bioinfodlsu/regulated-cell-death-playground
   

   Click to show/hide note for Windows users

   
   We recommend Windows users to avoid placing the cloned repository inside a deeply nested folder. The reason is that some scripts/notebooks (e.g., for the analysis of data from The Cancer Genome Atlas) require writing and reading files with long filenames. Dealing with Windows' 260-character path length limit can be quite tricky: https://blog.r-project.org/2023/03/07/path-length-limit-on-windows/

B. Downloading our dataset

1. Download our dataset from this link, and place it at the root of the cloned repository.

   Click to show/hide instructions for verifying the integrity of the downloaded dataset

   
   If you want to verify the integrity of the downloaded dataset, compute the SHA-512 checksum of the downloaded zipped folder using a hashing utility like certutil in Windows, shasum in Mac, or sha512sum in Linux. You should obtain the following checksum:
   
   

   checksum!

2. Extract the contents of the downloaded zipped folder. The extraction process should result in a folder named data, and inside it should be two folders: patient and public.

   Click here to show/hide the expected folder structure

   
   

   • regulated-cell-death-playground (root)
     • data
       • patient
       • public
     • analysis
     • ...

Note: If you prefer to run the entire pipeline for generating our dataset (instead of simply downloading it), refer to this section.

C. Running our analysis scripts and notebooks

Our analysis scripts and notebooks are written in R and found inside the analysis folder. Refer to this page for a description of each script/notebook.

The necessary dependencies can be set up following the instructions below:

1. Install the package manager renv by opening R and running:

   install.packages("renv")
   

2. Open R inside the analysis folder, and install the necessary dependencies by running:

   renv::restore()
   

   The dependencies (alongside their specifications) are listed in analysis/renv.lock.

🖇️ Running our dataset generation pipeline

This section is for users who would like to run the pipeline for generating our dataset. If you prefer to simply download our dataset, refer to this section.

Operating system: Linux or Windows (using WSL)

1. Install the package manager Conda. We recommend installing Miniconda.

2. Install the workflow management system Snakemake by running:

   conda create -c conda-forge -c bioconda -n snakemake snakemake
   

💻 Authors

• Mark Edward M. Gonzales
  [email protected]

• Kim Williame Lee
  [email protected]

• Dr. Anish M.S. Shrestha
  [email protected]

This is part of the "Investigating regulated necrotic cell death in colorectal cancer using a multi-omics approach" project funded by the Department of Science and Technology – Philippine Council for Health Research and Development (DOST-PCHRD). This project is led by Dr. Rafael A. Espiritu of the Department of Chemistry, College of Science, De La Salle University.