Galaxy tool discovery, intelligent recommendation, and execution — 8,000+ bioinformatics tools from usegalaxy.org with multi-signal scoring and workflow suggestions
ClawBio's gateway to the Galaxy ecosystem — 1,770+ production bioinformatics tools, discoverable and executable through natural language.
Galaxy (usegalaxy.org) hosts the world's largest collection of curated bioinformatics tools — 1,770+ on the main server alone, covering everything from FASTQ QC to metagenomics to protein structure prediction. But discovering the right tool requires knowing exact tool IDs, navigating nested ToolShed categories, and understanding parameter schemas.
Galaxy Bridge makes these tools agent-accessible: search by natural language, execute via CLI, and chain Galaxy tools with ClawBio's local skills for cross-platform workflows that neither system can do alone.
| Format | Extension | Required Fields | Example |
|---|---|---|---|
| FASTQ | .fq, .fastq, .fq.gz | Sequence reads | Illumina paired-end reads |
| VCF | .vcf, .vcf.gz | Variant calls | Annotated VCF for VEP |
| BAM | .bam | Aligned reads | BWA-MEM2 output |
| FASTA | .fa, .fasta | Sequences | Reference genome |
| Tabular | .tsv, .csv | Varies by tool | Gene expression matrix |
# Intelligent tool recommendation (new in v0.2.0)
python galaxy_bridge.py --recommend "quality control on my sequencing reads"
python galaxy_bridge.py --recommend "classify microbial species" --format .fastq
python galaxy_bridge.py --recommend "call variants" --format .bam
python galaxy_bridge.py --recommend "annotate variants from WES" --format .vcf
# Workflow / pipeline suggestions (new in v0.2.0)
python galaxy_bridge.py --workflow "RNA-seq differential expression"
python galaxy_bridge.py --workflow "metagenomics"
python galaxy_bridge.py --workflow "whole exome sequencing"
# Search for tools by keyword
python galaxy_bridge.py --search "metagenomics profiling"
python galaxy_bridge.py --search "variant annotation"
python galaxy_bridge.py --search "RNA-seq differential expression"
# Browse Galaxy ToolShed categories
python galaxy_bridge.py --list-categories
# View tool details (inputs, outputs, parameters)
python galaxy_bridge.py --tool-details toolshed.g2.bx.psu.edu/repos/devteam/fastqc/fastqc/0.74+galaxy1
# Run a tool on Galaxy (requires GALAXY_API_KEY)
python galaxy_bridge.py --run fastqc --input reads.fq.gz --output /tmp/qc_results
# Demo mode (works offline, no API key needed)
python galaxy_bridge.py --demo
The --recommend flag uses multi-signal scoring across 7 dimensions to rank tools:
| Signal | Max Points | Description |
|---|---|---|
| Section match | 30 | Tool's Galaxy category matches the detected task |
| Preferred tool | 20 | Tool is a known best-in-class for the task |
| Exact name match | 15 | Tool name appears in the query |
| Keyword match | 15 | Query words found in tool name/description |
| EDAM ontology | 10 | EDAM topic/operation IDs match the task |
| Format compatibility | 10 | Tool accepts the specified input format |
| Version maturity | 5 | Tools with more versions score higher (log scale) |
15 task categories are recognised: Quality Control, Read Mapping, Variant Calling, Variant Annotation, WES/WGS, RNA-seq, Metagenomics, Genome Assembly, Genome Annotation, Phylogenetics, ChIP-seq, Single-cell, Proteomics, Nanopore, BAM Processing.
8 workflow templates: WES Germline, WES Annotation, RNA-seq DE, Metagenomics Profiling, Variant Calling, ChIP-seq, Nanopore Assembly, Genome Assembly.
Running --demo executes a simulated FastQC analysis using pre-cached results:
$ python galaxy_bridge.py --demo
Galaxy Bridge — Demo Mode (offline)
====================================
Tool: FastQC v0.74+galaxy1
Input: demo/demo_reads.fq (bundled synthetic FASTQ, 1000 reads)
Output: demo/fastqc_demo_output.html
Result: PASS — Per base sequence quality ✓
PASS — Per sequence quality scores ✓
WARN — Per base sequence content (normal for Illumina)
PASS — Sequence length distribution ✓
Reproducibility bundle written to demo/reproducibility/
The bridge indexes tools across all 56 Galaxy ToolShed categories, including:
output_dir/
├── report.md # Analysis summary with methods and results
├── result.json # Machine-readable: tool ID, version, parameters, output paths
├── galaxy_outputs/ # Raw outputs downloaded from Galaxy
│ ├── fastqc_report.html
│ └── ...
└── reproducibility/
├── commands.sh # Galaxy API calls to reproduce
├── environment.yml # Tool versions and Galaxy server info
└── checksums.sha256 # SHA-256 of all inputs and outputs
Required:
Optional (for execution):
GALAXY_URL environment variable (default: https://usegalaxy.org)GALAXY_API_KEY environment variable (register at usegalaxy.org)galaxy_catalog.json — no API calls neededTriggers when: User mentions "galaxy", "usegalaxy", "tool shed", "run on galaxy", "NGS pipeline", or references a Galaxy tool ID.
Chaining partners:
pharmgx-reporter — Galaxy VEP annotates variants → PharmGx generates dosage reportclaw-metagenomics — Galaxy Kraken2 → ClawBio metagenomics profilingequity-scorer — Galaxy VCF processing → HEIM equity scoringvcf-annotator — Galaxy VEP/SnpSift ↔ ClawBio annotation