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Compute differential causal effects on (biological) networks. Check out our vignettes for more information.

Publication: https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btab847/6470558

Installation

Install the latest stable version from Bioconductor:

BiocManager::install("dce")

Install the latest development version from GitHub:

remotes::install_github("cbg-ethz/dce")

Project structure

  • .: R package
  • inst/scripts/: Snakemake workflows for all investigations in publication
    • crispr_benchmark: Real-life data validation
    • gtex_validation: Deconfounding validation
    • ovarian_cancer: How does Ovarian Cancer dysregulate pathways?
    • synthetic_benchmark: Synthetic data validation
    • tcga_pipeline: Compute effects for loads of data from TCGA

Development notes

  • Check package locally:
    • Rscript -e "lintr::lint_package()"
    • Rscript -e "devtools::test()"
    • Rscript -e "devtools::check(error_on = 'warning')"
    • R CMD BiocCheck
  • Documentation
    • Build locally: Rscript -e "pkgdown::build_site()"
    • Deploy: Rscript -e "pkgdown::deploy_to_branch(new_process = FALSE)"
  • Bioconductor
    • The bioc branch stores changes specific to Bioconductor releases
    • Update workflow (after git remote add upstream git@git.bioconductor.org:packages/dce.git):
      • git checkout bioc
      • git merge master
      • git push upstream bioc:master