arxiv-database
This skill provides Python tools for searching and retrieving preprints from arXiv.org via its public Atom API. It supports keyword search,…
Maintainer FreedomIntelligence · Last updated April 1, 2026
Statistical methods for calling hits in CRISPR screens. Covers MAGeCK, BAGEL2, drugZ, and custom approaches for identifying essential and resistance genes. Use when identifying significant genes from screen count data after QC passes.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-crispr-screens-hit-calling
Skill Snapshot
Source Doc
Goal: Identify essential genes using Bayesian classification against reference gene sets.
Approach: Calculate sgRNA fold changes, compute Bayes Factors using known essential and non-essential gene sets as training data, and assess precision-recall at different thresholds.
## Calculate Bayes Factor
bagel2 bf \
-i foldchange.txt \
-o bayes_factor.txt \
-e essential_genes.txt \
-n nonessential_genes.txt \
-c 1 # Number of bootstrap iterations
## Precision-recall analysis
bagel2 pr \
-i bayes_factor.txt \
-o precision_recall.txt \
-e essential_genes.txt \
-n nonessential_genes.txt
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