bio-workflows-riboseq-pipeline
End-to-end Ribo-seq analysis from FASTQ to translation efficiency and ORF detection. Use when analyzing ribosome profiling data to study translation.
npx skills add BioTender-max/awesome-bio-agent-skills --skill riboseq-pipeline --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: Bowtie2 2.5.3+, STAR 2.7.11+, cutadapt 4.4+, numpy 1.26+ 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. # Ribo-seq Pipeline **"Analyze my ribosome profiling data from FASTQ to translation efficiency"** → Orchestrate adapter trimming, rRNA depletion, genome alignment, periodicity QC, ORF detection (RiboCode), stalling analysis, and translation efficiency estimation (riborex). ## Pipeline Overview ``` FASTQ → Preprocessing → rRNA removal → Alignment → P-site → TE → ORF calling ``` ## Step 1: Preprocessing ```bash # Remove adapters cutadapt -a CTGTAGGCACCATCAAT \ --minimum-length 25 --maximum-length 35 \ -o trimmed.fastq.gz reads.fastq.gz # Remove rRNA bowtie2 -x rRNA_index --un non_rrna.fastq.gz -U trimmed.fastq.gz ``` ## Step 2: Alignment ```bash # Align to transcriptome STAR --genomeDir star_ind
- Version Compatibility
- Pipeline Overview
- Step 1: Preprocessing
- Step 2: Alignment
- Step 3: P-site Calibration
- Step 4: Translation Efficiency
- Step 5: ORF Detection
- Related Skills
Remove adapters cutadapt -a CTGTAGGCACCATCAAT \ Remove rRNA bowtie2 -x rRNA_index --un non_rrna.fastq.gz -U trimmed.fastq.gz Align to transcriptome STAR --genomeDir star_index \ RiboCode for ORF calling RiboCode -a annotation.gtf -c config.txt -o ribocoded_orfs
What does the bio-workflows-riboseq-pipeline skill do?
End-to-end Ribo-seq analysis from FASTQ to translation efficiency and ORF detection. Use when analyzing ribosome profiling data to study translation.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill riboseq-pipeline --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.