bio-small-rna-seq-mirdeep2-analysis
Discover novel miRNAs and quantify known miRNAs using miRDeep2 de novo prediction from small RNA-seq data. Use when identifying new miRNAs or performing comprehensive miRNA profiling with discovery.
npx skills add BioTender-max/awesome-bio-agent-skills --skill mirdeep2-analysis --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: 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. # miRDeep2 Analysis **"Discover novel miRNAs from my small RNA-seq data"** → Identify known and novel miRNAs by mapping reads to the genome and scoring precursor hairpin structures using a probabilistic model. - CLI: `mapper.pl` for read mapping, `miRDeep2.pl` for de novo miRNA prediction ## Workflow Overview ``` Collapsed reads (FASTA) | v mapper.pl ---------> Align to genome, create ARF file | v miRDeep2.pl -------> Predict novel miRNAs, quantify known | v quantifier.pl -----> Quantify known miRNAs only (optional) ``` ## Step 1: Prepare Genome Index **Goal:** Build a bowtie index from the reference genome for miRDeep2 read mapping. **Approach:** Run bowtie-build on the genome FASTA to create the index files required by mapper.pl. ```ba
- Version Compatibility
- Workflow Overview
- Step 1: Prepare Genome Index
- Step 2: Map Reads with mapper.pl
- Step 3: Run miRDeep2 Prediction
- Prepare miRBase References
- Step 4: Quantify Known miRNAs Only
- Output Files
- Interpret miRDeep2 Scores
- Parse Results in Python
- Related Skills
Build bowtie index for miRDeep2 mapper bowtie-build genome.fa genome_index Collapse reads and map to genome mapper.pl reads.fastq \ Key options: Predict novel miRNAs miRDeep2.pl \ reads_collapsed.fa \ genome.fa \ reads_vs_genome.arf \
What does the bio-small-rna-seq-mirdeep2-analysis skill do?
Discover novel miRNAs and quantify known miRNAs using miRDeep2 de novo prediction from small RNA-seq data. Use when identifying new miRNAs or performing comprehensive miRNA profiling with discovery.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill mirdeep2-analysis --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.