Agent skill · Workflow & Productivity

bio-crispr-screens-bagel-essentiality

Identifies essential genes from CRISPR-Cas9 fitness screens using BAGEL2 (Kim & Hart 2021 Genome Med), a Bayesian classifier scoring per-gene Bayes Factors via log-likelihood ratios over per-sgRNA fold changes, calibrated against CEGv2 core-essentials (Hart 2017 G3, ~684 genes) and NEGv1 non-essentials (Hart 2014, ~927 genes). Covers the fc + bf + pr workflow, the linear-extrapolation improvement over BAGEL1 truncation, multi-target off-target correction, tumor-suppressor sensitivity (BAGEL2 detects enrichment), and BF-to-FDR calibration (BF >6 ≈ FDR 0.05 from Hart 2017). Use when classifying

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill bagel-essentiality --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 14 KB
Bundled scripts: yes
Path: skills/bioskills/bagel-essentiality/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## Version Compatibility Reference examples tested with: BAGEL2 1.0.5+ (hart-lab/bagel), pandas 2.2+, numpy 1.26+, scipy 1.12+, matplotlib 3.8+. Before using code patterns, verify installed versions match. If versions differ: - CLI: `BAGEL.py fc --help`; `BAGEL.py bf --help`; `BAGEL.py pr --help` - Python: BAGEL2 is distributed via `git clone` (no canonical PyPI release); confirm `python BAGEL.py --version` after checkout. If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. ## BAGEL2 Essentiality Analysis **"Identify essential genes from my CRISPR fitness screen using BAGEL2"** -> Compute per-sgRNA fold changes from counts, derive per-gene log-likelihood ratios against reference essential and non-essential gene sets, sum to Bayes Factor, and apply BF threshold calibrated by precision-recall against the reference. - CLI: `BAGEL.py fc` to compute fold changes - CLI: `BAGEL.py bf` to compute Bayes Factors - CLI: `BAGEL.py pr` for precision-recall curves - Reference sets: CEGv2 (essentials) and NEGv1 (non-essentials); both at https://github.com/hart-lab/bagel ## The BAGEL2 Bayesia

What's inside
Steps it walks through
  1. Version Compatibility
  2. BAGEL2 Essentiality Analysis
  3. The BAGEL2 Bayesian Framework (under the hood)
  4. Calibration to CEGv2 / NEGv1
  5. Compute Per-Sample Fold Changes
  6. Compute Bayes Factors
  7. Precision-Recall Curve
  8. Interpret BAGEL2 Results
  9. Bayesian Reasoning Per Sgrna
  10. Comparing BAGEL2, MAGeCK, drugZ
  11. Failure Modes
  12. BAGEL2 returns no hits despite known essentials
  13. BAGEL2 calls negative-LFC genes "tumor suppressors"
  14. Bootstrap CI is wide; BF estimates unstable
Ships with 2 files
  • examples/run_bagel2.sh
  • usage-guide.md
Commands it runs
BAGEL2 installation: distributed via git clone (no canonical PyPI release).
git clone https://github.com/hart-lab/bagel
cd bagel
Some forks publish to PyPI (e.g. `bagel-cas9`) but the official distribution is the GitHub repo.
Control column(s): typically Day 0 or plasmid sample(s)
Treatment column(s): screen endpoint
BAGEL.py fc \
BAGEL.py bf \
BAGEL.py pr \
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About this skill
What does the bio-crispr-screens-bagel-essentiality skill do?

Identifies essential genes from CRISPR-Cas9 fitness screens using BAGEL2 (Kim & Hart 2021 Genome Med), a Bayesian classifier scoring per-gene Bayes Factors via log-likelihood ratios over per-sgRNA fold changes, calibrated against CEGv2 core-essentials (Hart 2017 G3, ~684 genes) and NEGv1 non-essentials (Hart 2014, ~927 genes). Covers the fc + bf + pr workflow, the linear-extrapolation improvement over BAGEL1 truncation, multi-target off-target correction, tumor-suppressor sensitivity (BAGEL2 detects enrichment), and BF-to-FDR calibration (BF >6 ≈ FDR 0.05 from Hart 2017). Use when classifying

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill bagel-essentiality --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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