multideconv

An integrative pipeline for combining first and second generation cell type deconvolution results

This repository contains the code to reproduce the analysis of the paper:

Hurtado, M., Essabbar, A., Khajavi, L., & Pancaldi, V. (2025). multideconv – Integrative pipeline for cell type deconvolution from bulk RNAseq using first and second generation methods. bioRxiv. https://doi.org/10.1101/2025.04.29.651220

Install from source

Clone the repository:

git clone https://github.com/VeraPancaldiLab/multideconv_paper

Project organization

• input/: Input files used during analysis (e.g. raw counts, metadata).
• output/: Intermediate files generated (e.g. deconvolution, subgroups).
• scripts/: Codes used for analysis.
  • Subgroups_analysis.Rmd: Subgroup analysis (Result: Grouped features preserve sample clustering structure and Grouping features preserves original data structure).
  • ML_analysis.Rmd: Analysis for Vanderbilt early stages samples (Result: Grouped features are highly predictive of immunotherapy response).
  • Metacells.Rmd: Metacell construction based on single cell data (Result: Validating subgrouped features using scRNAseq datasets).
  • Deconvolution_SC.Rmd: Deconvolution based on single cell (Result: Validating subgrouped features using scRNAseq datasets).
• Results/: Figures and generated cell signatures used in the paper.

Environment

If you would like to reproduce the analysis done here, we invite you to use our provided r-environment. Setting it up will install all the neccessary packages, along with their specific versions in an isolated environment.

For this, open the project multideconv_paper.Rproj inside the scripts/ folder and in the R console run:

# To activate the R environment (if you are using it for the first time)
renv::activate()
# To download and install all the require libraries and packages (if you are using it for the first time)
renv::restore() 

Once all packages have been installed, you can start testing the scripts but be sure to still be inside the .Rproj!

Note that this is an once-step only when running multideconv_paper for the first time. For the following times, you will only need to open the multideconv_paper.Rproj and you are ready to go!

Once all packages have been installed, you can start reproducing the analysis using the scripts inside the scripts/ folder.

Make sure to run renv::deactivate() when finishing, to avoid conflicts whenever you start a different R project.

For more information about how R-environments work, visit the main page of the tool renv.

R package

The multideconv R package and tutorials can be found at: https://github.com/VeraPancaldiLab/multideconv

Contributing

If you are interested or have questions about the analysis done in this project, we invite you to open an issue in https://github.com/VeraPancaldiLab/multideconv_paper/issues or contact Marcelo Hurtado ([email protected]) for more information.

Acknowledgements

This repository was created by Marcelo Hurtado in the Network Biology for Immuno-oncology (NetB(IO)²) group at the Cancer Research Center of Toulouse in supervision of Vera Pancaldi.