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Outputs of ProMaya

The ProMaya pipeline generates a highly structured output directory. By default, all results are written to results/promaya_nf/ (configurable via the --outdir parameter).

Output Directory Structure

results/promaya_nf/
├── master_predictions.tsv                 # 1. Primary aggregated results
├── predictions/
│   ├── <pair_id_1>/                       # 2. Pair-specific results
│   │   ├── probability.tsv
│   │   ├── logs/
│   │   │   └── prediction.log
│   │   ├── gradcam/                       # 3. Interpretability data (if --gradcam)
│   │   │   ├── protein_a_atoms.tsv
│   │   │   ├── protein_a_residue.tsv
│   │   │   ├── protein_a_surface.tsv
│   │   │   ├── interaction_pairs.tsv
│   │   │   └── top10_residue_correlation.tsv
│   │   ├── images/                        # 4. 2D Visualizations (if --gradcam)
│   │   │   └── *_attribution.png
│   │   └── structure/                     # 5. 3D Visualizations (if --gradcam)
│   │       ├── *_structure_graph.png
│   │       ├── *_correlation_heatmap.png
│   │       └── *_view.pml
│   └── <pair_id_N>/
├── disorder/                              # 6. Disorder scan results (if --run_disorder)
│   ├── <protein_basename_1>/
│   │   └── disorder_out/
│   │       ├── data/
│   │       │   └── *.tsv
│   │       └── images/
│   │           └── *.png
│   └── <protein_basename_N>/
└── pipeline_info/                         # 7. Nextflow provenance and reports
    ├── execution_report_<timestamp>.html
    ├── execution_timeline_<timestamp>.html
    ├── execution_trace_<timestamp>.txt
    └── pipeline_dag_<timestamp>.svg

Detailed File Descriptions

1. master_predictions.tsv

This is the primary output file you should consult first. It is an aggregated table containing the predictions for every pair processed in the run, sorted by interaction_probability in descending order.

Columns: - pair_id: The ID defined in your samplesheet. - protein_a / protein_b: Paths to the input structures. - checkpoint: The model checkpoint used. - interaction_probability: The raw sigmoid output (0.0 to 1.0). - threshold: The classification threshold used (default: 0.5). - predicted_interaction: Binary classification (1 if probability >= threshold, else 0).

2. Pair-Specific Data (predictions/<pair_id>/)

  • probability.tsv: The individual prediction file for this specific pair.
  • logs/prediction.log: Detailed execution log for the inference process, useful for debugging structural parsing issues (e.g., missing atoms, failed surface generation).

3. Interpretability Data (gradcam/)

Generated only if --gradcam true is active. These TSV files map the Graph Grad-CAM attribution scores back to the original physical structures. - protein_*_atoms.tsv: Attribution scores per atom. Identifies specific chemical groups driving the interaction. - protein_*_residue.tsv: Attribution scores aggregated per amino acid residue. - protein_*_surface.tsv: Attribution scores mapped to the generated solvent-accessible surface point cloud. - interaction_pairs.tsv: Cross-protein attention scores highlighting which residues on Protein A strongly interact with which residues on Protein B.

4. 2D Visualizations (images/)

  • *_attribution.png: Static 2D plots summarizing the distribution of attribution scores across the protein sequence.

5. 3D Visualizations (structure/)

  • *_correlation_heatmap.png: A 2D heatmap matrix visualizing the cross-protein attention between the top interacting residues.
  • *_view.pml: A dynamically generated PyMOL script. Opening this script in PyMOL will automatically load the PDB files and color the surfaces/ribbons according to the computed Grad-CAM attribution scores (red = high importance, blue = low importance).
  • *_structure_graph.png: A rendered PNG of the structures colored by attribution (requires PyMOL to be available in the execution environment).

6. Disorder Analysis (disorder/)

Generated only if --run_disorder true is active. - Contains raw TSV data and plotted PNG profiles of the intrinsic disorder probability across the sequence length of each unique protein, generated via IUPred2A/MetaPredict.

7. Pipeline Provenance (pipeline_info/)

Standard Nextflow reporting files containing execution times, memory/CPU utilization per process, and an interactive DAG visualization of the workflow.