tooluniverse-crispr-screen-analysis
Comprehensive CRISPR screen analysis for functional genomics. Analyze pooled or arrayed CRISPR screens (knockout, activation, interference) to identify essential genes, synthetic lethal interactions, and drug targets. Perform sgRNA count processing, gene-level scoring (MAGeCK, BAGEL), quality control, pathway enrichment, and drug target prioritization. Use for CRISPR screen analysis, gene essentiality studies, synthetic lethality detection, functional genomics, drug target validation, or identifying genetic vulnerabilities.
npx skills add BioTender-max/awesome-bio-agent-skills --skill tooluniverse-crispr-screen-analysis --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.
# ToolUniverse CRISPR Screen Analysis Comprehensive skill for analyzing CRISPR-Cas9 genetic screens to identify essential genes, synthetic lethal interactions, and therapeutic targets through robust statistical analysis and pathway enrichment. ## Overview CRISPR screens enable genome-wide functional genomics by systematically perturbing genes and measuring fitness effects. This skill provides an 8-phase workflow for: - Processing sgRNA count matrices - Quality control and normalization - Gene-level essentiality scoring (MAGeCK-like and BAGEL-like approaches) - Synthetic lethality detection - Pathway enrichment analysis - Drug target prioritization with DepMap integration - Integration with expression and mutation data ## Core Workflow ### Phase 1: Data Import & sgRNA Count Processing **Load sgRNA Count Matrix** ```python import pandas as pd import numpy as np def load_sgrna_counts(counts_file): """ Load sgRNA count matrix from MAGeCK format or generic TSV. Expected format: sgRNA | Gene | Sample1 | Sample2 | Sample3 | ... sgRNA_1 | BRCA1 | 1500 | 1200 | 1100 | ... sgRNA_2 | BRCA1 | 1800 | 1500 | 1400 | ... """ counts = pd.read_csv(counts_file, sep='\t') # Validate required columns r
- Overview
- Core Workflow
- Phase 1: Data Import & sgRNA Count Processing
- Phase 2: Quality Control & Filtering
- Phase 3: Normalization
- Phase 4: Gene-Level Scoring (MAGeCK-like)
- Phase 5: Synthetic Lethality Detection
- Phase 6: Pathway Enrichment Analysis
- Phase 7: Drug Target Prioritization
- Phase 8: Report Generation
- Advanced Use Cases
- Use Case 1: Genome-Wide Essentiality Screen
- Use Case 2: Synthetic Lethality Screen (KRAS)
- Use Case 3: Drug Target Discovery Pipeline
What does the tooluniverse-crispr-screen-analysis skill do?
Comprehensive CRISPR screen analysis for functional genomics. Analyze pooled or arrayed CRISPR screens (knockout, activation, interference) to identify essential genes, synthetic lethal interactions, and drug targets. Perform sgRNA count processing, gene-level scoring (MAGeCK, BAGEL), quality control, pathway enrichment, and drug target prioritization. Use for CRISPR screen analysis, gene essentiality studies, synthetic lethality detection, functional genomics, drug target validation, or identifying genetic vulnerabilities.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill tooluniverse-crispr-screen-analysis --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.