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linear-rna

linear-rna

Use PaddleHelix LinearRNA for LinearFold and LinearPartition RNA secondary-structure analysis, including extension build/import troubleshooting and safe input validation.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: linear-rna description: "Use PaddleHelix LinearRNA for LinearFold and LinearPartition RNA secondary-structure analysis, including extension build/import troubleshooting and safe input validation." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

LinearRNA

Use this sub-skill when a task mentions LinearRNA, LinearFold, LinearPartition, RNA secondary structure, RNA folding constraints, a missing linear_rna extension, or base-pair probability cutoffs.

Route

  • Use references/api-reference.md for linear_fold_c, linear_fold_v, linear_partition_c, linear_partition_v, beam size, bp_cutoff, constraints, return shapes, and small examples.
  • Use scripts/check_linear_rna.py before running user-supplied inputs; it validates RNA letters, constraint length and parentheses, canonical/wobble constrained pairs, beam_size, bp_cutoff, and extension importability.
  • Use references/build-and-troubleshooting.md when pahelix.toolkit.linear_rna, c.pahelix.toolkit.linear_rna.linear_rna, or a direct build-tree linear_rna module is missing, CMake fails, pybind11 is absent, Ninja/compiler tools are unavailable, or the deprecated sklearn dependency blocks installation.
  • Route protein, compound, docking, molecular generation, and broad PaddleHelix model workflows to the sibling sub-skill that owns that domain.

Safe Workflow

  1. Normalize the requested RNA sequence to uppercase RNA semantics; T is accepted as U, but ambiguous bases are not part of the documented LinearRNA API.
  2. For LinearFold constraints, require use_constraints=True, a constraint string with the same length as the sequence, only ?, ., (, ), balanced non-crossing parentheses, and constrained pairs compatible with AU, UA, CG, GC, GU, or UG.
  3. For LinearPartition, choose a bp_cutoff between 0.0 and 1.0; use a positive cutoff for exploratory checks to keep the pair list small.
  4. If the extension imports, run toy or user-approved inputs through scripts/check_linear_rna.py; use --model c for learned-parameter APIs and --model v for thermodynamic APIs. If import fails, diagnose the build route before attempting API calls.

Bundled Entry Points

python sub-skills/linear-rna/scripts/check_linear_rna.py --sequence GGGAAACCC --model c
python sub-skills/linear-rna/scripts/check_linear_rna.py --sequence GGGAAACCC --model v
python sub-skills/linear-rna/scripts/check_linear_rna.py --sequence UGAGUUCUCGAUCUCUAAAAUCG --partition --bp-cutoff 0.2 --model c
python sub-skills/linear-rna/scripts/check_linear_rna.py --sequence UGAGUUCUCGAUCUCUAAAAUCG --partition --bp-cutoff 0.2 --model v
python sub-skills/linear-rna/scripts/check_linear_rna.py --sequence GAAAC --constraint '(...)'

The script prints JSON on success and clear validation/import errors on failure. It does not download data, build the extension, mutate a checkout, or run large benchmark datasets.

Evidence Labels

This sub-skill distills the LinearRNA README, tutorial notebook examples, C++ pybind signatures, package build metadata, developer build notes, and environment-preparation caveats into self-contained references and a safe checker.

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