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contributing.md

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Including a new active module detection tool

  1. Create a new branch for your tool.
  2. Add a function to the bin/graph_tool_parser.py script for preparing the tool-specific network input format. The script is built around the graph-tool Python package. An example is the safe_diamond() function, which saves a simple edge list in CSV format. Add the function as an option in the save() function and a command line option for --format in parse_args(). The output file name has to include the option specified with --format since nextflow uses this pattern to check whether the output file was successfully generated. The script expects a .gt file as input. Run the pipeline with the "test" profile to generate a .gt example file in <OUTDIR>/graphtoolparser, which you can use to test the parsing function by executing the parsing script directly via the command line.
  3. Create a module for the tool. (Example with comments: modules/local/diamond/main.nf and modules/local/domino/)
  4. Create a subworkflow wrapping the tool together with the input parser. (Example with comments: subworkflows/local/gt_diamond/main.nf and subworkflows/local/gt_domino/main.nf)
  5. Include the subworkflow in the workflows/modulediscovery.nf file. Again, DIAMOnD and DOMINO are included as examples.
  6. Test checks locally:
    1. Run tests via, e.g., nextflow run main.nf -profile singularity,test --outdir results.
    2. Run nf-core lint.
    3. Check your code style. This will automatically happen before you commit, if you use pre-commit, which can be set up with: pre-commit install. After each commit, it will automatically check your code style and fix it where possible. If changes were made, you have to commit again.
  7. Create a pull request against the dev branch.

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