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CELIOS: extract omics data into integrated activity datasets for Boolean model calibration. Part of the DrugLogics and the TRAFIKK pipelines.

Project description

CELIOS

CEll LIne OmicS processor — extract omics data into integrated activity datasets for Boolean model calibration.

Python 3.8+ License: MIT

Used in the DrugLogics and TRAFIKK pipelines.


📊 What You Get

Node Dictionary (node_HGNC_dict.csv)

  • Network nodes mapped to HGNC gene symbols
  • Enables consistent gene annotation

Activity Master Matrix (activity_master_matrix.csv)

  • All omics data sources combined (mutations, CNV, TF, expression) for each node in the network across cell lines
  • Format: nodes × cell_lines__data_source

Priority-Filtered Activity (activity_from_master.csv)

  • One activity value per node-cell line (highest priority source)
  • Ready for downstream analysis

Per-Cell-Line Training Files (optional)

  • DrugLogics or Trafikk compatible format
  • Saved to cellfiles_dir/ if specified

Quick Start

Install:

pip install -e .

Run pipeline:

celios run --config config.yaml --verbose

Get help:

celios --help

📚 Documentation

Detailed documentation is in the documentation markdown files:

Document Purpose
QUICKSTART.md 5-minute quick reference with common commands
INSTALL.md Installation guide, virtual environments, troubleshooting
USAGE.md Full usage guide, advanced examples, and API reference
CONFIGURATION.md Configuration reference with all options
OUTPUTS.md Output file formats and interpretation
notebooks/ Interactive Jupyter notebooks with examples

Features

  • Step 1: Node dictionary generation from biological networks (SIF format)
  • Step 2: Cell-line identifier resolution and tissue-aware organization
  • Step 3: Multi-source omics integration (mutations, CNV, TF activity, expression)
  • Step 4: DrugLogics and Trafikk pipeline training file generation (specific calibration file used in the Gitsbe module)
  • Format support: Legacy CCLE (genes × SIDM) and 26Q1 (ModelID × genes) formats
  • Configuration-driven: JSON or YAML configs for easy reproducibility
  • Tissue organization: Optional per-tissue output structure for DrugLogics compatibility

License

MIT License

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