Agent skill · AI & Agents

bio-genome-annotation-ncrna-annotation

Identify non-coding RNAs including tRNAs, rRNAs, snoRNAs, and regulatory RNAs using Infernal covariance model searches against Rfam and tRNAscan-SE for tRNA prediction. Use when performing genome-wide ncRNA annotation with assembly input producing GFF output.

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

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

Facts
Files in the skill folder: 4
SKILL.md size: 10 KB
Bundled scripts: yes
Path: skills/bioskills/ncrna-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: pandas 2.2+ 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 If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Non-Coding RNA Annotation **"Find non-coding RNAs in my genome"** → Scan a genome assembly for rRNAs, tRNAs, snoRNAs, and other ncRNA families using covariance model search and specialized detectors. - CLI: `cmscan --rfam --tblout hits.tbl Rfam.cm assembly.fa` (Infernal), `tRNAscan-SE -o trnas.txt assembly.fa` Identify and annotate non-coding RNAs in genome assemblies using Infernal (general ncRNAs via Rfam covariance models) and tRNAscan-SE (specialized tRNA detection). ## Infernal / cmscan Infernal uses covariance models (CMs) from Rfam to identify ncRNA families by both sequence and secondary structure similarity. ### Rfam Database Setup ```bash # Download Rfam covariance models (~600 MB compressed) wget https://ftp.ebi.ac.uk/pub/da

What's inside
Steps it walks through
  1. Version Compatibility
  2. Infernal / cmscan
  3. Rfam Database Setup
  4. Basic cmscan
  5. Key Options
  6. Convert cmscan Output to GFF3
  7. E-value Guidelines
  8. tRNAscan-SE
  9. Basic Usage
  10. Domain-Specific Models
  11. Expected tRNA Counts
  12. barrnap (rRNA Detection)
  13. Combining ncRNA Annotations
  14. Troubleshooting
Ships with 3 files
  • examples/ncrna_annotation.sh
  • examples/parse_ncrna.py
  • usage-guide.md
Commands it runs
Download Rfam covariance models (~600 MB compressed)
wget https://ftp.ebi.ac.uk/pub/databases/Rfam/CURRENT/Rfam.cm.gz
gunzip Rfam.cm.gz
Press the CM database (required for cmscan)
cmpress Rfam.cm
Download clan information (for overlap resolution)
wget https://ftp.ebi.ac.uk/pub/databases/Rfam/CURRENT/Rfam.clanin
Search genome against all Rfam families
cmscan \
Rfam.cm \
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About this skill
What does the bio-genome-annotation-ncrna-annotation skill do?

Identify non-coding RNAs including tRNAs, rRNAs, snoRNAs, and regulatory RNAs using Infernal covariance model searches against Rfam and tRNAscan-SE for tRNA prediction. Use when performing genome-wide ncRNA annotation with assembly input producing GFF output.

How do I install it?

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

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