Individual skill
tooluniverse-crispr-screen-analysis
Analyze CRISPR-Cas9 genetic screens — MAGeCK gene-level scores, sgRNA count QC, replicate correlation, hit prioritization, and pathway GSEA on screen output. Use for genome-wide essentiality screens, synthetic-lethality discovery, dropout vs positive-selection screen analysis, target identification, and resistance-screen interpretation. Includes screen-QC and statistical thresholds.
plugin/skills/tooluniverse-crispr-screen-analysis/SKILL.md
Source commit 5598a9fc97e32964fe9b703818e7d0747142f179
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- Matches the observed repository HEAD
- Yes
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- No
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- Not checked yet
- Last checked
- Nov 5, 2026
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Repository context
- Repository stars (not skill ratings)
- 1,779
- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agents Repository topic
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- reasoning-language-models Repository topic
- tool-use Repository topic
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ANALYSIS_DETAILS.mddoc · 17,151 bytesEXAMPLES.mddoc · 12,270 bytesFALLBACK_PATCH.mddoc · 18,147 bytesQUICK_START.mddoc · 11,775 bytesSKILL.mdcore · 11,508 bytesSKILL.mdcore · 11,508 bytesUSE_CASES.mddoc · 4,309 bytesscripts/CEGv2_core_essential.txtdoc · 4,134 bytesscripts/NEGv1_nonessential.txtdoc · 6,086 bytesscripts/reference_gene_sets.pyruns · 1,966 bytes
Read excerpt
# ToolUniverse CRISPR Screen Analysis
## RULE ZERO — Check for pre-computed results FIRST
Before following any instruction below, scan the data folder for:
- `*_executed.ipynb` → read with `tu run read_executed_notebook '{"data_folder":"<path>","search":"<keyword>"}'` and cite its cell outputs as the authoritative answer
- Pre-computed result files (CSV/TSV with names like `*results*`, `*deseq*`, `*enrich*`, `*stats*`, `*_simplified.csv`) → read directly and report the requested value
- Canonical analysis scripts (`analysis.R`, `run_*.py`, `find_*.R`, `*.Rmd`) → execute as-is and read the output
Only follow this skill's re-analysis recipe below if **none** of the above exist. Re-running from raw data produces different numbers than the published answer and is much slower (often 5-10× turn count).
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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.