bio-single-cell-doublet-detection
bio-single-cell-doublet-detection is a Bioinformatics & life sciences skill for AI agents, published by GPTomics in the bioSkills repository on GitHub. Skillspace rates bio-single-cell-doublet-detection B (81/100) and it passed the safety scan; the rating is based on static analysis only.
Detect and remove doublets (two or more cells in one droplet) from single-cell RNA-seq using scDblFinder (R), Scrublet (Python), and DoubletFinder (R). Use when flagging artificial intermediate populations before clustering, setting the expected doublet rate from recovered-cell counts, running detection per sample before integration, choosing between simulate-and-score methods, or interpreting a non-bimodal score histogram.
- Grade
- B
- Quality
- 81 / 100
- Safety
- Passed
- GitHub stars
- 1,025
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
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 3 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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