hash_length: 7
containers:
  framework: docker
  unpack_singularity: false
  registry:
    base_url: docker.io
    owner: reedcompbio

algorithms:
  - name: "pathlinker"
    include: true
    runs:
      run1:
        k: [1, 10, 100, 1000]

  - name: omicsintegrator2
    include: true
    runs:
      run1:
        b: [4, 10]
        g: [0, 3]
        w: [0.25, 6]

  - name: mincostflow
    include: true
    runs:
      run1:
        capacity: [15, 30]
        flow: [80, 15]

  - name: "strwr"
    include: true
    runs:
      run1:
        alpha: 0.85
        threshold: [100, 200]

  - name: "rwr"
    include: true
    runs:
      run1:
        alpha: 0.85
        threshold: [100, 200]

datasets:
  - label: egfr
    node_files: ["tps-egfr-prizes.txt"]
    edge_files: ["phosphosite-irefindex13.0-uniprot.txt"]
    other_files: []
    data_dir: "input"

gold_standards:
  - # Labels can only contain letters, numbers, or underscores
    label: gs_egfr
    node_files: ["gs-egfr.txt"]
    data_dir: "input"
    # List of dataset labels to compare with the specific gold standard dataset
    dataset_labels: ["egfr"]

reconstruction_settings:
  locations:
    reconstruction_dir: "output/intermediate"

analysis:
  summary:
    include: false # set to true for step 4

  # Machine learning analysis (e.g. clustering) of the pathway output files for each dataset
  ml:
    # ml analysis per dataset
    include: false # set to true for step 3

    # adds ml analysis per algorithm output
    # only runs for algorithms with multiple parameter combinations chosen
    aggregate_per_algorithm: false # set to true for step 4
    # overalls a kernel density estimation over pca
    kde: false # set to true for step 4
    # removes empty pathways from consideration in ml analysis (pca only)
    remove_empty_pathways: false # set to true for step 4

  evaluation:
    # evaluation per dataset-goldstandard pair
    # evaluation will not run unless ml include is set to true
    include: false # set to true for step 4
    # adds evaluation per algorithm per dataset-goldstandard pair
    # evaluation per algorithm will not run unless ml include and ml aggregate_per_algorithm are set to true
    aggregate_per_algorithm: false # set to true for step 4
