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bio-crispr-screens-screen-qc

Assess library representation, read distribution, replicate correlation, and essential gene recovery in MAGeCK CRISPR screen outputs.

Updated Aug 23, 2026
Search Tags:#quality-control#screen#qc#crispr#replicate-correlation#essential-genes
One-click install
npx skills add https://github.com/stellaromics/fast-bioinfo --skill bio-crispr-screens-screen-qc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bio-crispr-screens-screen-qc
Source: https://github.com/stellaromics/fast-bioinfo/tree/main/.claude/agents/spatial-analysis/skills/bio-crispr-screens-screen-qc
Command: npx skills add https://github.com/stellaromics/fast-bioinfo --skill bio-crispr-screens-screen-qc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Quality control for pooled CRISPR screens, enabling quick assessment of library representation, read distribution, replicate concordance, and essential gene recovery to ensure reliable hit calling.

Core Features & Use Cases

  • Library Representation: Evaluate sgRNA coverage across samples to flag underrepresented libraries.
  • Read Distribution & Gini: Quantify uniform read distribution to identify skew and ensure data quality.
  • Replicate Correlation: Measure and visualize reproducibility between replicates to detect batch effects.
  • Essential Gene Recovery: Validate screen performance against known essential genes using AUROC or related metrics.
  • Use Case: Apply QC before hit calling to decide if the experiment should be re-run or include more replicates.

Quick Start

Run the QC workflow on your MAGeCK-derived results to obtain a concise report and diagnostics.

Frequently Asked Questions about bio-crispr-screens-screen-qc

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run quality control on a pooled CRISPR screen before hit calling?▼

Quality control for pooled CRISPR screens involves assessing library representation, read distribution, replicate concordance, and essential gene recovery to ensure reliable downstream hit calling.

What metrics indicate reliable pooled CRISPR screen quality?▼

Reliable pooled CRISPR screens require low Gini index values indicating uniform read distribution, high replicate correlations, and strong ROC-based essential gene recovery metrics to ensure robust hit calling.

How do I check essential gene recovery and replicate correlation in CRISPR screens?▼

You can check essential gene recovery using AUROC or related metrics against known essential genes, and measure replicate correlation by comparing sgRNA read distributions across replicates to detect batch effects.

Can I use MAGeCK output for CRISPR screen QC across multiple timepoints and replicates?▼

Yes, you can apply QC workflows directly to MAGeCK-derived count data to evaluate library representation and replicate concordance across standard CRISPR screens spanning multiple timepoints, replicates, and controls.

How many zero-count sgRNAs are acceptable in a pooled CRISPR library representation?▼

Pooled CRISPR library QC flags underrepresented libraries by measuring zero-count sgRNAs. High numbers of zero-count guides indicate poor library representation and suggest the experiment may need to be re-run.

When should I re-run a CRISPR screen based on quality control diagnostics?▼

You should re-run a CRISPR screen when QC diagnostics reveal severe read distribution skew, poor replicate correlations, or failed essential gene recovery, indicating insufficient data quality for reliable hit calling.

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