bio-crispr-screens-library-design
Designs pooled sgRNA libraries for CRISPR knockout, interference (CRISPRi), activation (CRISPRa), Cas12a multiplex, base-editor, and prime-editor screens. Covers on-target scoring (Rule Set 2, Azimuth, DeepSpCas9, CRISPRon), off-target scoring (CFD, MIT), TSS-relative positioning for CRISPRi/a (Horlbeck, Dolcetto, Calabrese), PAM-variant chemistries, control-guide composition, oligo cloning architecture, and library QC. Use when choosing a genome-wide library (GeCKOv2 vs Avana vs Brunello vs TKOv3 vs Inzolia), designing a focused or paralog-focused custom library, picking CRISPRi vs CRISPRa TS
npx skills add BioTender-max/awesome-bio-agent-skills --skill library-design --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: CRISPOR 5.01+, BioPython 1.83+, pandas 2.2+, numpy 1.26+, Azimuth 2.0+ (Doench 2016), CRISPRon 1.0+ (Xiang 2021), DeepSpCas9 1.0+ (Kim 2019). Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show crispor` then `help(...)` to check signatures - CLI: `crispor.py --help`, `azimuth --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. ## sgRNA Library Design **"Design a CRISPR library for my screen"** -> Pick a chemistry (Cas9 KO, CRISPRi, CRISPRa, Cas12a, base or prime editor), score candidate guides for on-target activity and off-target liability, position them relative to gene/TSS, add appropriate controls, lay out the oligo for synthesis, and validate the cloned pool. - Python: `crispor.py` (web + CLI) for batch genome-wide guide scoring with CFD+MIT off-target - Python: `azimuth` (Microsoft Research) for Rule Set 2 on-target predictions (Brunello-style) - Python: `CRISPRon`, `DeepSpCas9` for modern deep-learning predictors - R: `crisprDesign` (Biocond
- Version Compatibility
- sgRNA Library Design
- Library Chemistry Decision Tree
- On-Target Scoring: Algorithmic Taxonomy
- Off-Target Scoring
- Score and Rank sgRNAs for a Target Gene
- CRISPRi / CRISPRa TSS Targeting
- Genome-Wide Library Selection
- PAM Variants and Alternative Cas Enzymes
- Control Guides
- Library Composition for Specialized Screens
- Oligo Design for Pooled Synthesis
- Library QC After Cloning
- Failure Modes
What does the bio-crispr-screens-library-design skill do?
Designs pooled sgRNA libraries for CRISPR knockout, interference (CRISPRi), activation (CRISPRa), Cas12a multiplex, base-editor, and prime-editor screens. Covers on-target scoring (Rule Set 2, Azimuth, DeepSpCas9, CRISPRon), off-target scoring (CFD, MIT), TSS-relative positioning for CRISPRi/a (Horlbeck, Dolcetto, Calabrese), PAM-variant chemistries, control-guide composition, oligo cloning architecture, and library QC. Use when choosing a genome-wide library (GeCKOv2 vs Avana vs Brunello vs TKOv3 vs Inzolia), designing a focused or paralog-focused custom library, picking CRISPRi vs CRISPRa TS
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill library-design --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.