scatac-preprocessing
scatac-preprocessing is a Bioinformatics & life sciences skill for AI agents, published by mdbabumiamssm in the LLMs-Universal-Life-Science-and-Clinical-Skills- repository on GitHub. Skillspace rates scatac-preprocessing D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Single-cell ATAC-seq preprocessing with a Signac-style TF-IDF + LSI workflow. Performs cell and peak filtering, top-peak selection, TF-IDF normalization, latent semantic indexing, neighborhood graph construction, UMAP, and Leiden clustering, then exports a downstream-ready AnnData plus a standard OmicsClaw gallery and reproducibility bundle.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 30
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
- 77 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 1 collections
Not checked yet
- Category is a classifier prediction; no model has read this skill 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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