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BHKLAB-DataProcessing/CTRP-Pharmacoset_Snakemake
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# A pipeline for processing the CTRP data ## This pipeline uses the `pixi` package manager Clone this repository and then run: ```bash pixi install ``` This makes sure that the lock is synchronized and version controlled. ## Usage To add packages to the `default` environment: ```bash pixi add pandas ``` ### To run a command in the environment ```bash pixi run snakemake --dryrun ``` ### Enter into the environment ```bash pixi shell # Exit the environment using "exit" ``` ### Pixi Tasks Pixi also allows defining tasks for common tasks. This is done in the [pyproject.toml](pyproject.toml) file. ```toml [tool.pixi.tasks] dryrun = "snakemake --dry-run" snake = "snakemake --cores 1" ``` This allows me to run `pixi run dryrun` to see what snakemake would do and `pixi run snake` to run snakemake. A common task I like to do is creating the dags regularly and including them in my README. This can then be automated with the task. ```toml dag = "snakemake -F --dag | dot -Tsvg > resources/dag.svg" rulegraph = "snakemake -F --rulegraph | dot -Tsvg > resources/rulegraph.svg" filegraph = "snakemake -F --filegraph | dot -Tsvg > resources/filegraph.svg" graphs = { depends_on = ["dag", "rulegraph", "filegraph"] } ``` Running `pixi run graphs` will create the three graphs and save them in the resources folder. This way, they are automatically updated below in this README. #### DAG ![DAG](resources/dag.svg) #### Rulegraph ![Rulegraph](resources/rulegraph.svg) #### Filegraph ![Filegraph](resources/filegraph.svg)
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