Data & ReproStatistics & Data AnalysisFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction
BI

bio-crispr-screens-mageck-analysis

Maintainer FreedomIntelligence · Last updated April 1, 2026

MAGeCK (Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout) for pooled CRISPR screen analysis. Covers count normalization, gene ranking, and pathway analysis. Use when identifying essential genes, drug targets, or resistance mechanisms from dropout or enrichment screens.

OpenClawNanoClawAnalysisReproductionbio-crispr-screens-mageck-analysis🧬 bioinformatics (gptomics bio-* suite)bioinformatics — epidemiological & causal genomicsmageck

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-crispr-screens-mageck-analysis

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • CLI: mageck count → mageck test for standard analysis.
  • CLI: mageck mle for multi-condition designs.
  • Analyze my pooled CRISPR screen with MAGeCK" → Count sgRNA reads, normalize across samples, and rank genes by enrichment or depletion using the MAGeCK robust rank aggregation algorithm. CLI: mageck count → mageck test for standard analysis CLI: mageck mle for multi-condition designs.
  • mageck count \ -l library.csv \ -n experiment \ --sample-label Day0,Treated1,Treated2,Control1,Control2 \ --fastq Day0.fastq.gz Treated1.fastq.gz Treated2.fastq.gz Control1.fastq.gz Control2.fastq.gz \ --norm-method median.

Source Doc

Excerpt From SKILL.md

Count sgRNAs from FASTQ

Goal: Quantify sgRNA representation from raw sequencing data.

Approach: Map FASTQ reads to the sgRNA library sequences with MAGeCK count, producing a normalized count matrix and QC summary across all samples.


## library.csv (tab-separated)

sgRNA_ID	Gene	Sequence
BRCA1_1	BRCA1	ATGGATTTATCTGCTCTTCG
BRCA1_2	BRCA1	CAGCAGATACTTGATGCATC
TP53_1	TP53	CCATTGTTCAATATCGTCCG
...

MAGeCK Test (RRA Algorithm)

Goal: Identify genes significantly enriched or depleted between treatment and control conditions.

Approach: Run MAGeCK test with robust rank aggregation, which ranks sgRNAs by fold change, tests whether per-gene sgRNA rankings deviate from uniform, and reports gene-level significance with FDR correction.

Use cases

  • Use when identifying essential genes, drug targets, or resistance mechanisms from dropout or enrichment screens.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

Upstream Related Skills

  • screen-qc - Quality control before MAGeCK
  • hit-calling - Alternative hit calling methods
  • pathway-analysis/gsea - Downstream enrichment analysis

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