Autonomous bioinformatics analysis platform running on a high-performance server (160 cores, 2.2 TiB RAM, Ubuntu 24.04).
Hermes provides a set of Snakemake workflows orchestrated via an MCP server, allowing Claude to plan, execute, and monitor bioinformatics analyses end-to-end.
| Workflow | Analysis Type | Key Tools |
|---|---|---|
genome_annotation |
Genome QC + Repeat + BRAKER4 + Functional | BUSCO, RepeatModeler, BRAKER4, DIAMOND, InterPro |
rnaseq |
RNA-seq differential expression | STAR, featureCounts, DESeq2, clusterProfiler |
atacseq |
ATAC-seq peak calling | Bowtie2, MACS3, DiffBind |
scrnaseq |
Single-cell RNA-seq clustering + markers | STARsolo, scDblFinder, Scanpy, Leiden |
wgs_snp |
WGS SNP/INDEL calling (non-model organisms) | fastp, BWA-MEM2, DeepVariant (GPU), GLnexus, SNPeff |
snp_association |
SNP-trait GWAS + Fst scan | PLINK2, GEMMA LMM, VCFtools Fst, CMplot |
pool_seq |
Pool-seq allele frequency + Fst scan | fastp, BWA-MEM2, bcftools, Hudson Fst (R) |
All workflows use standardized CSV samplesheets. See samplesheet_template.csv in each workflow directory.
sample,r1,r2
sample_001,/path/to/sample_001_R1.fastq.gz,/path/to/sample_001_R2.fastq.gzsample_id,phenotype,weight_g,length_cm
fish_001,1,52.3,16.1
fish_031,0,41.7,14.5hermes/
├── mcp_server.py # MCP server (tools: run_workflow, get_status, etc.)
├── setup_hermes.sh # Environment setup script
├── CLAUDE.md # Agent instructions
└── workflows/
├── wgs_snp/
├── snp_association/
├── rnaseq/
├── scrnaseq/
├── atacseq/
└── genome_annotation/
Databases : /home/cylin/Vet_Hamaguri/databases/
FCS-GX DB : /home/cylin/Vet_Hamaguri/FCS_DB
Workflow runs : /home/cylin/hermes/runs/<run_id>/
- Snakemake ≥ 8
- Conda / Mamba
- Docker (for DeepVariant GPU)
- NVIDIA GPU + CUDA (for
wgs_snpDeepVariant step) - Claude Code with MCP server configured