tooluniverse-functional-genomics-screens

name	tooluniverse-functional-genomics-screens
description	Interpret hits from CRISPR-KO/CRISPRi/shRNA screens by integrating DepMap essentiality, gnomAD constraint scores, pathway context (Reactome, STRING), druggability (DGIdb), and clinical evidence (CIViC, COSMIC). Use for screen-hit prioritization, essentiality ranking, and turning a list of screen hits into a prioritized target shortlist.
disable-model-invocation	true

Functional Genomics Screen Interpretation

Pipeline for validating and prioritizing hits from genetic screens (CRISPR-KO, CRISPRi, shRNA) by integrating essentiality (DepMap), constraint (gnomAD), pathways (Reactome, STRING), druggability (DGIdb), and clinical evidence (CIViC, COSMIC).

Guiding principles:

1. Hits are hypotheses -- screen results contain false positives; validate through orthogonal evidence
2. Selectivity matters -- pan-essential genes are poor drug targets; context-specific essentiality is high-value
3. Pathway over gene -- enriched pathways are more robust than individual hits
4. Druggability is practical -- prioritize chemically modulable targets
5. English-first queries -- use English gene names in tool calls

LOOK UP, DON'T GUESS

When uncertain about any scientific fact, SEARCH databases first.

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COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.