bio-crispr-screens-screen-qc
Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / B
npx skills add BioTender-max/awesome-bio-agent-skills --skill screen-qc --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: MAGeCK 0.5+ (count + VISPR), MAGeCKFlute 2.0+ (R), pandas 2.2+, numpy 1.26+, scikit-learn 1.4+, matplotlib 3.8+, seaborn 0.13+. Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show mageck` then `mageck count --help`; `pip show mageckflute` - R: `packageVersion('MAGeCKFlute')` then `?BatchRemove` / `?FluteRRA` If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. ## CRISPR Screen Quality Control **"Audit my CRISPR screen quality before hit calling"** -> Assess library representation, replicate concordance, depth, drift, and biological signal recovery using DepMap-grade metrics, then decide whether the screen is usable, salvageable, or must be repeated. - Python: `pandas` + `scikit-learn` for Gini, AUC, PCA; `MAGeCKFlute` (R) for one-shot QC dashboard - CLI: `mageck count` `--gini`, `--mapping_summary` flags; MAGeCK-VISPR for interactive dashboard ## QC Stage Hierarchy A pooled screen has six distinct bottlenecks where complexity can collapse. Audit each: | Stage | Metric | Acc
- Version Compatibility
- CRISPR Screen Quality Control
- QC Stage Hierarchy
- Library Representation Metrics
- Gini Coefficient
- Replicate Concordance
- Essentialome Recovery (CEGv2 PR-AUC)
- Copy-Number Amplicon Bias Diagnostic
- Sequencing Depth Audit
- MOI Verification
- PCA and Batch Effect Detection
- Composite DepMap-Style Quality Score
- Failure Modes
- High Gini in plasmid pool despite passing all design rules
What does the bio-crispr-screens-screen-qc skill do?
Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / B
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill screen-qc --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.