Agent skill · Databases

bio-variant-annotation

Comprehensive variant annotation using bcftools annotate/csq, VEP, SnpEff, and ANNOVAR. Add database annotations, predict functional consequences, and assess clinical significance with MANE transcript selection and pathogenicity scoring. Use when annotating variants with functional and clinical information.

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

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

Facts
Files in the skill folder: 3
SKILL.md size: 16 KB
Bundled scripts: yes
Path: skills/bioskills/variant-annotation/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: bcftools 1.19+, VEP 110+, SnpEff 5.2+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags - Note: SnpEff and SnpSift use single-dash `-version`, not `--version` If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Variant Annotation ## Tool Comparison | Tool | Best For | Speed | Output | |------|----------|-------|--------| | bcftools csq | Simple consequence prediction | Fast | VCF | | VEP | Comprehensive with plugins | Moderate | VCF/TXT | | SnpEff | Fast batch annotation | Fast | VCF | | ANNOVAR | Flexible databases | Moderate | TXT | ## Normalization Before Annotation Variant normalization is mandatory before annotation. The same variant represented differently (e.g., left-aligned vs right-aligned indels, multiallelic vs biallelic) produces different annotations. Always normalize first: ```bash bcftools norm -f reference.fa -m-any input.vcf.gz -O

What's inside
Steps it walks through
  1. Version Compatibility
  2. Tool Comparison
  3. Normalization Before Annotation
  4. Transcript Selection Strategy
  5. Tool Concordance
  6. Clinical vs Research Annotation
  7. bcftools annotate
  8. Add Annotations from Database
  9. Annotation Columns (-c)
  10. Add Multiple Annotations
  11. Add from BED/TAB Files
  12. Remove Annotations
  13. Set ID from Fields
  14. bcftools csq
Ships with 2 files
  • examples/annotate_vcf.sh
  • usage-guide.md
Commands it runs
bcftools norm -f reference.fa -m-any input.vcf.gz -Oz -o normalized.vcf.gz
bcftools annotate -a dbsnp.vcf.gz -c ID input.vcf.gz -Oz -o annotated.vcf.gz
bcftools annotate -a database.vcf.gz -c ID,INFO/AF,INFO/CAF input.vcf.gz -Oz -o annotated.vcf.gz
BED with 4th column as annotation
bcftools annotate -a regions.bed.gz -c CHROM,FROM,TO,INFO/REGION \
input.vcf.gz -Oz -o annotated.vcf.gz
Tab file: CHROM POS VALUE
bcftools annotate -a annotations.tab.gz -c CHROM,POS,INFO/SCORE \
bcftools annotate -x INFO/DP,INFO/MQ input.vcf.gz -Oz -o clean.vcf.gz
bcftools annotate -x INFO input.vcf.gz -Oz -o minimal.vcf.gz  # Remove all INFO
More from awesome-bio-agent-skills
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About this skill
What does the bio-variant-annotation skill do?

Comprehensive variant annotation using bcftools annotate/csq, VEP, SnpEff, and ANNOVAR. Add database annotations, predict functional consequences, and assess clinical significance with MANE transcript selection and pathogenicity scoring. Use when annotating variants with functional and clinical information.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill variant-annotation --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.

Keep going