This is a tool for pathway analysis of proteomic and phosphoproteomic datasets. CausalPath aims to identify mechanistic pathway relations that can explain observed correlations in experiments
Additional information about CausalPath can be found @ https://github.com/PathwayAndDataAnalysis/causalpath
A work-in-progress manuscript describing this method is available here.
If you simply want to use this workflow, download and extract the latest release. If you intend to modify and further develop this workflow, fork this reposity. Please consider providing any generally applicable modifications via a pull request.
In any case, if you use this workflow in a paper, don't forget to give credits to the authors by citing the URL of this repository and, once available, its DOI.
Configure the workflow according to your needs via editing the file omic_config.yaml.
All you need to execute this workflow is to install Snakemake via the Conda package manager. Software needed by this workflow is automatically deployed into isolated environments by Snakemake.
Test your configuration by performing a dry-run via
snakemake --use-conda -n
Execute the workflow locally via
snakemake --use-conda --cores $N
using $N cores. Alternatively, it can be run in cluster or cloud environments (see the docs for details).
If you not only want to fix the software stack but also the underlying OS, use
snakemake --use-conda --use-singularity
in combination with any of the modes above.
After successful execution, you can create a self-contained report with all results via:
snakemake --report report.html