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Galaxy Bridge
ClawBio's gateway to the Galaxy ecosystem — 1,770+ production bioinformatics tools, discoverable and executable through natural language.
Why This Exists
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.
Core Capabilities
Intelligent tool recommendation — describe a task in plain English; multi-signal scoring across 7 dimensions returns the best Galaxy tool with explanationsWorkflow suggestions — 8 pre-defined pipeline templates (RNA-seq DE, metagenomics, variant calling, WES germline, ChIP-seq, nanopore, genome assembly, variant annotation)Input format awareness — provide your file extension (.fastq, .bam, .vcf) for format-aware recommendationsVersion deduplication — 8,182 catalog entries collapse to ~2,300 unique tools; latest version preferred, version count as maturity signalEDAM ontology resolution — 108 EDAM topic/operation IDs resolved to human-readable labels for richer matchingNatural language search — keyword-based search across 8,000+ Galaxy tools by name, description, section, and EDAM termsRemote execution — run Galaxy tools on usegalaxy.org via BioBlend APICategory browsing — explore 86 ToolShed categories with tool countsTool detail inspection — view inputs, outputs, and parameter schemasOffline demo mode — FastQC demo with pre-cached results (no API key needed)
Cross-platform chaining — Galaxy VEP → ClawBio PharmGx, Galaxy Kraken2 → ClawBio metagenomics
Input Formats Format Extension Required Fields Example FASTQ .fq, .fastq, .fq.gzSequence reads Illumina paired-end reads VCF .vcf, .vcf.gzVariant calls Annotated VCF for VEP BAM .bamAligned reads BWA-MEM2 output FASTA .fa, .fastaSequences Reference genome Tabular .tsv, .csvVaries by tool Gene expression matrix
Workflow
Search — User describes what they need → bridge searches local catalog + Galaxy APISelect — Ranked results with descriptions, versions, and categoriesConfigure — Show tool inputs/outputs schema; user provides files and parametersExecute — Upload input to Galaxy, run tool, poll for completionRetrieve — Download outputs to local directoryBundle — Generate reproducibility package (commands.sh, environment.yml, checksums)
CLI Reference # 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
Recommendation Engine 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.
Demo 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/
Galaxy Tool Categories The bridge indexes tools across all 56 Galaxy ToolShed categories, including:
Sequence Analysis (~30 tools): FastQC, Trimmomatic, Cutadapt, fastpMetagenomics (~25 tools): Kraken2, MetaPhlAn, HUMAnN, QIIME2Variant Analysis (~25 tools): VEP, SnpSift, BCFtools, FreeBayesRNA (~20 tools): HISAT2, StringTie, featureCounts, DESeq2Proteomics (~15 tools): MaxQuant, SearchGUI, PeptideShakerPhylogenetics (~15 tools): IQ-TREE, RAxML, MAFFT, MUSCLEGenome Annotation (~15 tools): Prokka, Augustus, MAKERAssembly (~15 tools): SPAdes, Flye, Unicycler, MEGAHITSingle Cell (~10 tools): Scanpy, CellRanger, SeuratChIP-seq/Epigenetics (~10 tools): MACS2, deepTools, DiffBindGWAS (~10 tools): PLINK, REGENIE, BOLT-LMMNanopore (~10 tools): NanoPlot, Medaka, minimap2
Output Structure 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
Dependencies
Python 3.9+
bioblend (Galaxy Python SDK)
Optional (for execution):
GALAXY_URL environment variable (default: https://usegalaxy.org)GALAXY_API_KEY environment variable (register at usegalaxy.org)
Safety
Local-first search : Tool discovery uses the bundled galaxy_catalog.json — no API calls neededAPI key optional : Demo mode and search work without credentialsNo data retention : Uploaded files are deleted from Galaxy after output retrievalReproducibility : Every execution generates a full provenance bundleDisclaimer : ClawBio is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions.
Integration with Bio Orchestrator Triggers when : User mentions "galaxy", "usegalaxy", "tool shed", "run on galaxy", "NGS pipeline", or references a Galaxy tool ID.
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
Citations 