qcp-omics 0.1.1

Quality control, preprocessing and analysis of omics data for machine learning

QCP-Omics

1. Before you run the tool

1.1. Prepare metadata

1. Create a metadata.json file
2. If you plan to run the tool interactively, then only provide "dtypes" inside:

{
  "dtypes": {
    "feature1": "type",
    "feature2": "type"
  }
}

Note:

• "dtypes" must represent data types for all of the columns/features of your dataset. In case some of them are missing, a validation error will occur.
• If you choose interactive mode and still provide other fields in this file, they will be ignored.

3. If you want to specify all you metadata then look at section 2.2.

2. Install and run the tool

1. Create a virtual environment: python3 -m venv .venv
2. Activate it: source .venv/bin/activate
3. Install the package manager: pip install poetry
4. Install all dependencies: poetry install
5. Ensure you can run the tool: qcp

2.1. Running with interactive input

If you want to run the tool by interactively providing information about your dataset then simply run qcp interactive and answer the prompts.

2.2. Running with a prepared metadata.json file

If you wish to run the tool directly by providing all the input in a metadata.json file, then make sure it contains all of the following fields:

{
  "dataset_type": "clinical | genomics | proteomics",
  "dataset_path": "dataset/path",
  "metadata_path": "metadata/path",
  "output_path": "output/path",
  "features_cols": false,
  "en_header": true,
  "all_numeric": false,
  "is_raw": true,
  "steps_to_run": ["step 1", "step 2"],
  "dtypes": {
    "feature1": "type",
    "feature2": "type"
  }
}