scrna-meta-analysis
scrna-meta-analysis is a Bioinformatics & life sciences skill for AI agents, published by ammawla in the encode-toolkit repository on GitHub. Skillspace rates scrna-meta-analysis D (69/100) and it passed the safety scan; the rating is based on static analysis only.
Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility, TIN-based quality filtering, and detection-limit-aware interpretation. Handles batch correction (Harmony/Seurat), dropout awareness, cross-contamination artifacts, and platform-specific biases. Use this skill for ANY scRNA-seq integration task, cross-dataset comparison, cell atlas construction, or reproducibility assessment involving ENCODE single-cell data.
- Grade
- D
- Quality
- 69 / 100
- Safety
- Passed
- GitHub stars
- 37
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
- 90 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- AGPL-3.0
- Adoption
- Adopted by 0 other repositories, in 1 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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