bio-genome-annotation-eukaryotic-gene-prediction
Predict protein-coding genes in eukaryotic genomes using BRAKER3 for combined RNA-seq and protein evidence, or GALBA for protein-only evidence. Runs Augustus with trained parameters for accurate gene models. Use when annotating a newly assembled eukaryotic genome or improving existing gene predictions.
npx skills add BioTender-max/awesome-bio-agent-skills --skill eukaryotic-gene-prediction --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: BUSCO 5.5+, HISAT2 2.2.1+, pandas 2.2+, samtools 1.19+ 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. # Eukaryotic Gene Prediction **"Predict genes in my eukaryotic genome"** → Identify protein-coding gene structures (exons, introns, UTRs) using RNA-seq alignment evidence and/or protein homology to train ab initio predictors. - CLI: `braker.pl --genome=assembly.fa --bam=rnaseq.bam --prot_seq=proteins.fa` (BRAKER3) Predict protein-coding genes in eukaryotic genomes using evidence-based methods. BRAKER3 combines RNA-seq and protein homology evidence for the most accurate predictions. GALBA provides an alternative when only protein evidence is available. ## Prerequisites **CRITICAL:** The input assembly must be softmasked (repeats in lowercase). Run repeat-annotation first to softmask the genome. U
- Version Compatibility
- Prerequisites
- BRAKER3 (RNA-seq + Protein Evidence)
- Evidence Preparation
- Run BRAKER3
- Key Options
- Output Files
- GALBA (Protein-Only Evidence)
- When to Use GALBA vs BRAKER3
- Augustus Standalone
- Evaluation with BUSCO
- Interpretation
- Python: Parse Gene Models
- Troubleshooting
Align RNA-seq with HISAT2 hisat2-build assembly_softmasked.fasta genome_index hisat2 -x genome_index -1 reads_R1.fastq.gz -2 reads_R2.fastq.gz \ samtools index rnaseq_sorted.bam Download OrthoDB proteins for the relevant clade wget https://bioinf.uni-greifswald.de/bioinf/partitioned_odb11/Viridiplantae.fa.gz gunzip Viridiplantae.fa.gz braker.pl \ galba.pl \ List available pre-trained species
What does the bio-genome-annotation-eukaryotic-gene-prediction skill do?
Predict protein-coding genes in eukaryotic genomes using BRAKER3 for combined RNA-seq and protein evidence, or GALBA for protein-only evidence. Runs Augustus with trained parameters for accurate gene models. Use when annotating a newly assembled eukaryotic genome or improving existing gene predictions.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill eukaryotic-gene-prediction --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.