single-cell-encode
single-cell-encode is a Bioinformatics & life sciences skill for AI agents, published by ammawla in the encode-toolkit repository on GitHub. Skillspace rates single-cell-encode D (61/100) and it passed the safety scan; the rating is based on static analysis only.
Find and work with ENCODE single-cell genomics data including scRNA-seq and scATAC-seq. Use when the user asks about single-cell experiments, cell type resolution, clustering from ENCODE data, deconvolution of bulk signals using single-cell references, or comparing single-cell vs bulk profiles. Covers platform differences (10X Chromium, Smart-seq2, Drop-seq), quality limitations of single-cell data, multimodal integration (RNA+ATAC), and cross-study reproducibility concerns. Also use for cell type annotation, gene detection limits, dropout artifacts, and single-cell data structure in ENCODE.
- Grade
- D
- Quality
- 61 / 100
- Safety
- Passed
- GitHub stars
- 24
Unproven: rated by static analysis only, not yet compared head-to-head.
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Our review
- Architecture
- 87 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
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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