bio-rna-structure-ncrna-search
Searches for non-coding RNA homologs and classifies RNA families using Infernal covariance model searches against the Rfam database. Identifies structured RNAs by sequence and secondary structure conservation. Use when querying sequences against Rfam, building custom covariance models for novel RNA families, or classifying non-coding transcripts by family.
npx skills add BioTender-max/awesome-bio-agent-skills --skill ncrna-search --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: BioPython 1.83+, Infernal 1.1+, 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. # ncRNA Search **"Search my sequences for known non-coding RNA families"** → Query sequences against the Rfam database using covariance models that score both sequence and secondary structure conservation, or build custom CMs for novel RNA families. - CLI: `cmscan` for searching against Rfam CMs - CLI: `cmbuild` + `cmcalibrate` for building custom covariance models Search for non-coding RNA homologs and classify RNA families using covariance models (CMs). Infernal scores both sequence and secondary structure conservation, making it more sensitive than sequence-only methods for structured RNAs. ## Rfam Database Setup ```bash # Download current Rfam covariance models (~500 MB compressed) wget https://ftp.ebi
- Version Compatibility
- Rfam Database Setup
- cmscan: Query Sequences Against Rfam
- cmscan Key Options
- Gathering Threshold vs E-value
- cmsearch: Search Specific CM Against Sequence Database
- Building Custom Covariance Models
- Step 1: Prepare Stockholm Alignment
- Step 2: Build and Calibrate
- Step 3: Search
- cmbuild Options
- Parsing Infernal Output
- Tabular Output (--tblout --fmt 2)
- Extract Hit Sequences
Download current Rfam covariance models (~500 MB compressed) wget https://ftp.ebi.ac.uk/pub/databases/Rfam/CURRENT/Rfam.cm.gz gunzip Rfam.cm.gz Press the CM database (required before searching) cmpress Rfam.cm Download clan information (for resolving overlapping hits) wget https://ftp.ebi.ac.uk/pub/databases/Rfam/CURRENT/Rfam.clanin Basic cmscan against Rfam cmscan --cpu 8 --tblout results.tbl --fmt 2 Rfam.cm query.fa > results.out With clan overlap resolution (removes redundant hits from same clan)
What does the bio-rna-structure-ncrna-search skill do?
Searches for non-coding RNA homologs and classifies RNA families using Infernal covariance model searches against the Rfam database. Identifies structured RNAs by sequence and secondary structure conservation. Use when querying sequences against Rfam, building custom covariance models for novel RNA families, or classifying non-coding transcripts by family.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill ncrna-search --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.