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GEMDeCan

GEMDeCan: Gene Expression and Methylation based Deconvolution for Cancer

Welcome to the GEMDeCan repository

You will find here a snakemake pipeline to perform immune cell type deconvolution using 6 methods and 12 signatures based on gene expression and methylation data.

Organization

  • inputs : Directory where your inputs are located along with the signatures files used in the pipeline.
  • results : Directory where your output will be saved. cibersortx/ is where CibersortX results are saved, deconvolutions/ is where results from all the other methods without CibersortX are saved and all_deconvolutions/ is where all deconvolution results merged are saved.
  • scripts : Directory where you will find all the scripts produce to run the pipeline

Using GEMDeCan

Input file

  • Gene expression matrix: TPM normalized in .txt format

Format specification

gene    Sample1   Sample2   Sample3
 g1      1.8       5.2       4.1
 g2      5.7       8.3       2.0
 g3      6.2       3.1       9.2
 g4      7.2       9.1       0.6

Once this format is achieved, you can save the input file from R using:

write.table(counts.TPM.normalized, "GEMDeCan_deconvolution/inputs/file_name.txt", quote = F, sep = "\t", row.names = F)

Note that the input file should be saved in inputs/ directory. Additionally, go to the snakemake.yml file and add the name of your input file (without extension) in the Mixtures section.

Installation

Snakemake allows for a very efficient and user friendly way of using pipelines. It is designed so all you need to install is mamba which is required to install Snakemake Note that officially only Linux is supported for this pipeline. This also requires an Internet connection in order to use mamba auto-generated environments for all necessary software and packages.

Mamba

  • Linux curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname -m).sh" bash Mambaforge-$(uname)-$(uname -m).sh

Snakemake

  • Linux conda activate base mamba install snakemake -n base -c conda-forge -c bioconda

Linux packages sudo apt install build-essential sudo apt-get install r-base-dev sudo apt-get install -y libtiff5-dev zlib1g-dev libpng-dev libxml2-dev libharfbuzz-dev libfribidi-dev libcurl4-openssl-dev libfontconfig1-dev liblapack-dev libopenblas-dev

Docker (If not already installed)

  • Linux sudo apt install ca-certificates curl gnupg lsb-release sudo mkdir -p /etc/apt/keyrings curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg sudo chmod a+r /etc/apt/keyrings/docker.gpg echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null sudo apt update sudo apt install docker-ce docker-ce-cli containerd.io

R packages

After running GEMDeCan succesfully for the first time, go to the files scripts/run_cibersort_local_container.R, scripts/merge_all_deconvolutions.R and scripts/deconvolution/deconvolution_algorithms.R and uncomment the first lines to avoid re-looking for them in the future.

Configure your workspace

  • Input file should be save in folder inputs/
  • Go to the file snakemake.yml and add the name of your input file in the section Mixtures

Run GEMDeCan

Either sudo snakemake --cores 8 all or sudo path_where_snakemake_is_located --cores 8 all depending if snakemake has been installed locally or not.

CIBERSORTX

CIBERSORTx is included in the deconvolution methods in the GEMDeCan pipeline, but it's not run by default as it's not an open-source program.

To run it, please ask for a token in CibersortX and create a file named credentials.txt with your username and password on separate lines.

MAIL: [email protected]
TOKEN: token_passowrd123

Citation

To cite the pipeline, refer to our paper on BiorXiv :
GEM-DeCan: Improved tumor immune microenvironment profiling through novel gene expression and DNA methylation signatures predicts immunotherapy response
Ting Xie, Jacobo Solorzano, Miguel Madrid-Mencía, Abdelmounim Essabbar, Julien Pernet, Mei-Shiue Kuo, Alexis Hucteau, Alexis Coullomb, Nina Verstraete, Olivier Delfour, Francisco Cruzalegui, Vera Pancaldi bioRxiv 2021.04.09.439207; doi: https://doi.org/10.1101/2021.04.09.439207

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