tooluniverse-variant-predictor-dms-validation
tooluniverse-variant-predictor-dms-validation is a Bioinformatics & life sciences skill for AI agents, published by mims-harvard in the ToolUniverse repository on GitHub. Skillspace rates tooluniverse-variant-predictor-dms-validation D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Validate a variant-effect predictor (AlphaMissense, ESM-C SAE, ESM logits, EVE, conservation scores, or any per-variant numeric score) against experimental deep mutational scanning (DMS) data. Computes per-variant predictor scores, splits variants into neutral vs disruptive groups by DMS effect, runs a Mann-Whitney U test on the predictor scores, and sweeps the stratification thresholds for robustness. Use when you need to know whether a predictor's scores track real functional disruption on a specific protein.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 1,566
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 2 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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