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@@ -151,9 +151,64 @@ After each run, `<samplesheet_folder>` contains:
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## End-to-end loop
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0.**Bootstrap the datasets** – run `oncodrive3d build-datasets --mane_only` to generate the MANE-only baseline and mapping files, and run `oncodrive3d build-datasets --mane` (or a default `build-datasets`) if you also wish to retrieve structures from the canonical AlphaFold download (recommended).
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0.**Initialize the datasets** – run `oncodrive3d build-datasets --mane_only` to generate the MANE-only baseline and mapping files, and run `oncodrive3d build-datasets --mane` (or a default `build-datasets`) if you also wish to retrieve structures from the canonical AlphaFold download (recommended).
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1.**Prepare the missing set** – run `prepare_samplesheet.py`.
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2.**Harvest canonical matches (optional)** – invoke `update_samplesheet_and_structures.py` with `--canonical-dir` to reuse any AlphaFold canonical structures and shrink the missing set before prediction.
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3.**Predict the remaining structures** – run nf-core/proteinfold on `missing/samplesheet.csv` + `missing/fasta/`.
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4.**Ingest predictions** – re-run `update_samplesheet_and_structures.py` with `--predicted-dir` (and optionally `--canonical-dir` again) to fold new PDBs into `predicted/` and refresh the missing set.
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5.**Rebuild Oncodrive3D datasets** – point `oncodrive3d build-datasets --mane_only` at `final_bundle/pdbs` (`--custom_mane_pdb_dir`) and `final_bundle/samplesheet.csv` (`--custom_mane_metadata_path`) so every subsequent `oncodrive3d run` benefits from the extended MANE coverage.
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