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bio-crispr-screens-jacks-analysis
维护者 FreedomIntelligence · 最近更新 2026年4月1日
bio-crispr-screens-jacks-analysis：JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens) ，用于 modeling sgRNA efficacy 、 gene essentiality。 适合在analyzing multiple CRISPR screens simultaneously 或 when accounting ，用于 variable sgRNA efficiency across experiments时使用。
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-crispr-screens-jacks-analysis
- 维护者
- FreedomIntelligence
- 许可
- MIT
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- Python：jacks.infer_JACKS() ，用于 joint analysis across experiments。
- 分析 multiple CRISPR screens jointly ，支持 JACKS" → Model sgRNA efficacy 、 gene essentiality simultaneously across multiple screens，accounting ，用于 variable guide efficiency. Python：jacks.infer_JACKS() ，用于 joint analysis across experiments。
- JACKS jointly models sgRNA efficacy 、 gene essentiality across multiple experiments. It infers both gene-level fitness effects 、 sgRNA-specific efficiency。
- git clone https：//github.com/felicityallen/JACKS.git cd JACKS && pip install -e。
原始文档
SKILL.md 摘录
counts.txt (tab-separated)
sgRNA Gene Sample1 Sample2 Sample3 Control1 Control2 sgRNA1 GENE_A 100 120 90 80 85 sgRNA2 GENE_A 200 180 210 150 160 sgRNA3 GENE_B 50 45 55 60 58 ...
## replicatemap.txt
Sample1 Experiment1 Day14
Sample2 Experiment1 Day14
Sample3 Experiment2 Day14
Control1 Experiment1 Day0
Control2 Experiment2 Day0
guidemap.txt
sgRNA1 GENE_A sgRNA2 GENE_A sgRNA3 GENE_B sgRNA4 GENE_B ...
适用场景
- 适合在analyzing multiple CRISPR screens simultaneously 或 when accounting ，用于 variable sgRNA efficiency across experiments时使用。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
上游相关技能
- mageck-analysis - Alternative screen analysis method
- hit-calling - Statistical hit identification
- screen-qc - Quality control before analysis
- batch-correction - Handle batch effects in multi-screen data
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