Bioinformatics Skills Gateway: 400+ Genomics Skills for Hermes

This optional Hermes skill turns a vague request about genomics, sequencing, or computational biology into a concrete plan by pointing the agent at two large open-source skill libraries. It does not bundle hundreds of domain skills itself; it indexes them and fetches the specific reference or pipeline you need on demand. Reach for it when a task touches variant calling, RNA-seq, single-cell work, protein structure, pharmacogenomics, metagenomics, phylogenetics, or any other computational biology problem and you want expert-level parameters rather than generic advice.

What it does

The gateway sits between Hermes and two upstream repositories. bioSkills holds 385 reference skills: code patterns, parameter guides, and decision trees, written as a SKILL.md file per topic with examples in Python, R, and CLI. ClawBio holds 33 runnable pipeline skills: executable Python scripts with demos, where each analysis exports a report.md, a commands.sh, and an environment.yml so the run can be reproduced.

In practice you identify the domain and skill name from the index, clone the relevant repo shallowly into the Hermes cache, read the specific skill file, and then treat it as an expert domain guide. The fetched material contains correct parameters, proper tool flags, and validated pipelines, but it is not in Hermes SKILL.md format. The agent reads it as reference, not as an executable Hermes skill.

Before you start

This skill is optional and installed on demand. It is version 1.0.0, authored by Teknium (teknium1) at Hermes Agent, MIT licensed, and listed for linux and macos only.

The upstream libraries assume a bioinformatics workstation. The source lists common dependencies for Python, R/Bioconductor, and CLI tools, plus a Conda route that is recommended for reproducibility. You do not need all of them before cloning, but you do need the tools a given skill calls for before running its pipeline. The source is explicit that both repos assume bioinformatics tools are installed and that you should check prerequisites before running pipelines.

Fetching a skill

The workflow has four steps. First, identify the domain and skill name from the index below. Second, clone the relevant repo with a shallow clone to save time:

# bioSkills (reference material)
git clone --depth 1 https://github.com/GPTomics/bioSkills.git ~/.hermes/cache/scratch/bioSkills

# ClawBio (runnable pipelines)
git clone --depth 1 https://github.com/ClawBio/ClawBio.git ~/.hermes/cache/scratch/ClawBio

Third, read the specific skill. bioSkills stores each skill at <category>/<skill-name>/SKILL.md; ClawBio stores each at skills/<skill-name>/:

# bioSkills — each skill is at: <category>/<skill-name>/SKILL.md
cat ~/.hermes/cache/scratch/bioSkills/variant-calling/gatk-variant-calling/SKILL.md

# ClawBio — each skill is at: skills/<skill-name>/
cat ~/.hermes/cache/scratch/ClawBio/skills/pharmgx-reporter/README.md

Fourth, follow the fetched skill as reference material. These are not Hermes-format skills. Treat them as expert domain guides containing correct parameters, proper tool flags, and validated pipelines.

Skill index by domain

The index is the map you use in step one. Each domain lists bioSkills categories and, where available, ClawBio pipelines.

Sequence fundamentals

bioSkills: sequence-io/, read-sequences, write-sequences, format-conversion, batch-processing, compressed-files, fastq-quality, filter-sequences, paired-end-fastq, sequence-statistics sequence-manipulation/, seq-objects, reverse-complement, transcription-translation, motif-search, codon-usage, sequence-properties, sequence-slicing ClawBio: seq-wrangler, Sequence QC, alignment, and BAM processing (wraps FastQC, BWA, SAMtools)

Read QC and alignment

bioSkills: read-qc/, quality-reports, fastp-workflow, adapter-trimming, quality-filtering, umi-processing, contamination-screening, rnaseq-qc read-alignment/, bwa-alignment, star-alignment, hisat2-alignment, bowtie2-alignment alignment-files/, sam-bam-basics, alignment-sorting, alignment-filtering, bam-statistics, duplicate-handling, pileup-generation

Variant calling and annotation

bioSkills: variant-calling/, gatk-variant-calling, deepvariant, variant-calling (bcftools), joint-calling, structural-variant-calling, filtering-best-practices, variant-annotation, variant-normalization, vcf-basics, vcf-manipulation, vcf-statistics, consensus-sequences, clinical-interpretation ClawBio: vcf-annotator, VEP + ClinVar + gnomAD annotation with ancestry-aware context variant-annotation, Variant annotation pipeline

Differential expression (bulk RNA-seq)

bioSkills: differential-expression/, deseq2-basics, edger-basics, batch-correction, de-results, de-visualization, timeseries-de rna-quantification/, alignment-free-quant (Salmon/kallisto), featurecounts-counting, tximport-workflow, count-matrix-qc expression-matrix/, counts-ingest, gene-id-mapping, metadata-joins, sparse-handling ClawBio: rnaseq-de, Full DE pipeline with QC, normalization, and visualization diff-visualizer, Rich visualization and reporting for DE results

Single-cell RNA-seq

bioSkills: single-cell/, preprocessing, clustering, batch-integration, cell-annotation, cell-communication, doublet-detection, markers-annotation, trajectory-inference, multimodal-integration, perturb-seq, scatac-analysis, lineage-tracing, metabolite-communication, data-io ClawBio: scrna-orchestrator, Full Scanpy pipeline (QC, clustering, markers, annotation) scrna-embedding, scVI-based latent embedding and batch integration

Spatial transcriptomics

bioSkills: spatial-transcriptomics/, spatial-data-io, spatial-preprocessing, spatial-domains, spatial-deconvolution, spatial-communication, spatial-neighbors, spatial-statistics, spatial-visualization, spatial-multiomics, spatial-proteomics, image-analysis

Epigenomics

bioSkills: chip-seq/, peak-calling, differential-binding, motif-analysis, peak-annotation, chipseq-qc, chipseq-visualization, super-enhancers atac-seq/, atac-peak-calling, atac-qc, differential-accessibility, footprinting, motif-deviation, nucleosome-positioning methylation-analysis/, bismark-alignment, methylation-calling, dmr-detection, methylkit-analysis hi-c-analysis/, hic-data-io, tad-detection, loop-calling, compartment-analysis, contact-pairs, matrix-operations, hic-visualization, hic-differential ClawBio: methylation-clock, Epigenetic age estimation

Pharmacogenomics and clinical

bioSkills: clinical-databases/, clinvar-lookup, gnomad-frequencies, dbsnp-queries, pharmacogenomics, polygenic-risk, hla-typing, variant-prioritization, somatic-signatures, tumor-mutational-burden, myvariant-queries ClawBio: pharmgx-reporter, PGx report from 23andMe/AncestryDNA (12 genes, 31 SNPs, 51 drugs) drug-photo, Photo of medication → personalized PGx dosage card (via vision) clinpgx, ClinPGx API for gene-drug data and CPIC guidelines gwas-lookup, Federated variant lookup across 9 genomic databases gwas-prs, Polygenic risk scores from consumer genetic data nutrigx_advisor, Personalized nutrition from consumer genetic data

Population genetics and GWAS

bioSkills: population-genetics/, association-testing (PLINK GWAS), plink-basics, population-structure, linkage-disequilibrium, scikit-allel-analysis, selection-statistics causal-genomics/, mendelian-randomization, fine-mapping, colocalization-analysis, mediation-analysis, pleiotropy-detection phasing-imputation/, haplotype-phasing, genotype-imputation, imputation-qc, reference-panels ClawBio: claw-ancestry-pca, Ancestry PCA against SGDP reference panel

Metagenomics and microbiome

bioSkills: metagenomics/, kraken-classification, metaphlan-profiling, abundance-estimation, functional-profiling, amr-detection, strain-tracking, metagenome-visualization microbiome/, amplicon-processing, diversity-analysis, differential-abundance, taxonomy-assignment, functional-prediction, qiime2-workflow ClawBio: claw-metagenomics, Shotgun metagenomics profiling (taxonomy, resistome, functional pathways)

Genome assembly and annotation

bioSkills: genome-assembly/, hifi-assembly, long-read-assembly, short-read-assembly, metagenome-assembly, assembly-polishing, assembly-qc, scaffolding, contamination-detection genome-annotation/, eukaryotic-gene-prediction, prokaryotic-annotation, functional-annotation, ncrna-annotation, repeat-annotation, annotation-transfer long-read-sequencing/, basecalling, long-read-alignment, long-read-qc, clair3-variants, structural-variants, medaka-polishing, nanopore-methylation, isoseq-analysis

Structural biology and chemoinformatics

bioSkills: structural-biology/, alphafold-predictions, modern-structure-prediction, structure-io, structure-navigation, structure-modification, geometric-analysis chemoinformatics/, molecular-io, molecular-descriptors, similarity-searching, substructure-search, virtual-screening, admet-prediction, reaction-enumeration ClawBio: struct-predictor, Local AlphaFold/Boltz/Chai structure prediction with comparison

Proteomics

bioSkills: proteomics/, data-import, peptide-identification, protein-inference, quantification, differential-abundance, dia-analysis, ptm-analysis, proteomics-qc, spectral-libraries ClawBio: proteomics-de, Proteomics differential expression

Pathway analysis and gene networks

bioSkills: pathway-analysis/, go-enrichment, gsea, kegg-pathways, reactome-pathways, wikipathways, enrichment-visualization gene-regulatory-networks/, scenic-regulons, coexpression-networks, differential-networks, multiomics-grn, perturbation-simulation

Immunoinformatics

bioSkills: immunoinformatics/, mhc-binding-prediction, epitope-prediction, neoantigen-prediction, immunogenicity-scoring, tcr-epitope-binding tcr-bcr-analysis/, mixcr-analysis, scirpy-analysis, immcantation-analysis, repertoire-visualization, vdjtools-analysis

CRISPR and genome engineering

bioSkills: crispr-screens/, mageck-analysis, jacks-analysis, hit-calling, screen-qc, library-design, crispresso-editing, base-editing-analysis, batch-correction genome-engineering/, grna-design, off-target-prediction, hdr-template-design, base-editing-design, prime-editing-design

Workflow management

bioSkills: workflow-management/, snakemake-workflows, nextflow-pipelines, cwl-workflows, wdl-workflows ClawBio: repro-enforcer, Export any analysis as reproducibility bundle (Conda env + Singularity + checksums) galaxy-bridge, Access 8,000+ Galaxy tools from usegalaxy.org

Specialized domains

bioSkills: alternative-splicing/, splicing-quantification, differential-splicing, isoform-switching, sashimi-plots, single-cell-splicing, splicing-qc ecological-genomics/, edna-metabarcoding, landscape-genomics, conservation-genetics, biodiversity-metrics, community-ecology, species-delimitation epidemiological-genomics/, pathogen-typing, variant-surveillance, phylodynamics, transmission-inference, amr-surveillance liquid-biopsy/, cfdna-preprocessing, ctdna-mutation-detection, fragment-analysis, tumor-fraction-estimation, methylation-based-detection, longitudinal-monitoring epitranscriptomics/, m6a-peak-calling, m6a-differential, m6anet-analysis, merip-preprocessing, modification-visualization metabolomics/, xcms-preprocessing, metabolite-annotation, normalization-qc, statistical-analysis, pathway-mapping, lipidomics, targeted-analysis, msdial-preprocessing flow-cytometry/, fcs-handling, gating-analysis, compensation-transformation, clustering-phenotyping, differential-analysis, cytometry-qc, doublet-detection, bead-normalization systems-biology/, flux-balance-analysis, metabolic-reconstruction, gene-essentiality, context-specific-models, model-curation rna-structure/, secondary-structure-prediction, ncrna-search, structure-probing

Data visualization and reporting

bioSkills: data-visualization/, ggplot2-fundamentals, heatmaps-clustering, volcano-customization, circos-plots, genome-browser-tracks, interactive-visualization, multipanel-figures, network-visualization, upset-plots, color-palettes, specialized-omics-plots, genome-tracks reporting/, rmarkdown-reports, quarto-reports, jupyter-reports, automated-qc-reports, figure-export ClawBio: profile-report, Analysis profile reporting data-extractor, Extract numerical data from scientific figure images (via vision) lit-synthesizer, PubMed/bioRxiv search, summarization, citation graphs pubmed-summariser, Gene/disease PubMed search with structured briefing

Database access

bioSkills: database-access/, entrez-search, entrez-fetch, entrez-link, blast-searches, local-blast, sra-data, geo-data, uniprot-access, batch-downloads, interaction-databases, sequence-similarity ClawBio: ukb-navigator, Semantic search across 12,000+ UK Biobank fields clinical-trial-finder, Clinical trial discovery

Experimental design

bioSkills: experimental-design/, power-analysis, sample-size, batch-design, multiple-testing

Machine learning for omics

bioSkills: machine-learning/, omics-classifiers, biomarker-discovery, survival-analysis, model-validation, prediction-explanation, atlas-mapping ClawBio: claw-semantic-sim, Semantic similarity index for disease literature (PubMedBERT) omics-target-evidence-mapper, Aggregate target-level evidence across omics sources

Environment setup

The source lists common dependencies for a bioinformatics workstation. Install what your chosen skill needs; the Conda route is recommended for reproducibility.

# Python
pip install biopython pysam cyvcf2 pybedtools pyBigWig scikit-allel anndata scanpy mygene

# R/Bioconductor
Rscript -e 'BiocManager::install(c("DESeq2","edgeR","Seurat","clusterProfiler","methylKit"))'

# CLI tools (Ubuntu/Debian)
sudo apt install samtools bcftools ncbi-blast+ minimap2 bedtools

# CLI tools (macOS)
brew install samtools bcftools blast minimap2 bedtools

# Or via Conda (recommended for reproducibility)
conda install -c bioconda samtools bcftools blast minimap2 bedtools fastp kraken2

When not to use it

The source does not present this gateway as a replacement for a dedicated Hermes skill. It is a router to external reference material. If your task is a single narrow question that a general model can answer without domain-specific parameters, cloning a repo adds overhead. If you need an executable Hermes skill rather than a guide, this is not that: the fetched skills use their own structure and are not in Hermes SKILL.md format.

Limits and gotchas

The source lists several caveats worth repeating in full. The fetched skills are not in Hermes SKILL.md format; they use their own structure, with bioSkills as code pattern cookbooks and ClawBio as README plus Python scripts. Read them as expert reference material. bioSkills are reference guides that show correct parameters and code patterns but are not executable pipelines. ClawBio skills are executable, and many have --demo flags and can be run directly. Both repos assume bioinformatics tools are installed, so check prerequisites before running pipelines. For ClawBio, run pip install -r requirements.txt in the cloned repo first. Genomic data files can be very large, so be mindful of disk space when downloading reference genomes, SRA datasets, or building indices.

What pairs with it

The source points to the two upstream repositories as the related resources: bioSkills at https://github.com/GPTomics/bioSkills and ClawBio at https://github.com/ClawBio/ClawBio. Use the first for reference patterns and the second for runnable pipelines that export reproducibility bundles.