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Bioinformatics

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Tommy-yw
bioinformatics

Gateway to 400+ bioinformatics skills from bioSkills and ClawBio. Covers genomics, transcriptomics, single-cell, variant calling, pharmacogenomics, metagenomics, structural biology, and more. Fetches domain-specific reference material on demand.

Overview

PublisherTommy-yw
RepositoryRunbookHermes
Skill namebioinformatics
Stars
546
Forks
41
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Tommy-yw on GitHub. Read the source before you install it.

Installation

Install the Bioinformatics AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Tommy-yw/RunbookHermes/tree/main/optional-skills/research/bioinformatics
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Tommy-yw/RunbookHermes.git /tmp/RunbookHermes
mkdir -p .claude/skills
cp -r /tmp/RunbookHermes/optional-skills/research/bioinformatics .claude/skills/bioinformatics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bioinformatics in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bioinformatics on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bioinformatics is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Bioinformatics Skills Gateway

Use when asked about bioinformatics, genomics, sequencing, variant calling, gene expression, single-cell analysis, protein structure, pharmacogenomics, metagenomics, phylogenetics, or any computational biology task.

This skill is a gateway to two open-source bioinformatics skill libraries. Instead of bundling hundreds of domain-specific skills, it indexes them and fetches what you need on demand.

Sources

◆ bioSkills — 385 reference skills (code patterns, parameter guides, decision trees) Repo: https://github.com/GPTomics/bioSkills Format: SKILL.md per topic with code examples. Python/R/CLI.

◆ ClawBio — 33 runnable pipeline skills (executable scripts, reproducibility bundles) Repo: https://github.com/ClawBio/ClawBio Format: Python scripts with demos. Each analysis exports report.md + commands.sh + environment.yml.

How to fetch and use a skill

  1. Identify the domain and skill name from the index below.
  2. Clone the relevant repo (shallow clone to save time):
    bash
    # bioSkills (reference material)
    git clone --depth 1 https://github.com/GPTomics/bioSkills.git /tmp/bioSkills
    
    # ClawBio (runnable pipelines)
    git clone --depth 1 https://github.com/ClawBio/ClawBio.git /tmp/ClawBio
  3. Read the specific skill:
    bash
    # bioSkills — each skill is at: <category>/<skill-name>/SKILL.md
    cat /tmp/bioSkills/variant-calling/gatk-variant-calling/SKILL.md
    
    # ClawBio — each skill is at: skills/<skill-name>/
    cat /tmp/ClawBio/skills/pharmgx-reporter/README.md
  4. Follow the fetched skill as reference material. These are NOT Hermes-format skills — treat them as expert domain guides. They contain correct parameters, proper tool flags, and validated pipelines.

Skill Index by Domain

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 & 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 & 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 & 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 & 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 & 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 & 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 & 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 & 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 & 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 & 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

These skills assume a bioinformatics workstation. Common dependencies:

bash
# 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

Pitfalls

  • The fetched skills are NOT in Hermes SKILL.md format. They use their own structure (bioSkills: code pattern cookbooks; ClawBio: README + Python scripts). Read them as expert reference material.
  • bioSkills are reference guides — they show correct parameters and code patterns but aren't executable pipelines.
  • ClawBio skills are executable — many have --demo flags and can be run directly.
  • Both repos assume bioinformatics tools are installed. 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. Be mindful of disk space when downloading reference genomes, SRA datasets, or building indices.

Frequently asked questions

What does the Bioinformatics AI skill do?

Gateway to 400+ bioinformatics skills from bioSkills and ClawBio. Covers genomics, transcriptomics, single-cell, variant calling, pharmacogenomics, metagenomics, structural biology, and more. Fetches domain-specific reference material on demand.

Why use Bioinformatics on TypingMind?

Because you install it once and use it with any model. Bioinformatics is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bioinformatics in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Tommy-yw/RunbookHermes/tree/main/optional-skills/research/bioinformatics. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bioinformatics?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bioinformatics?

As many as you like. As long as a model supports skills, you can use Bioinformatics with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bioinformatics AI skill free?

Yes. It is published on GitHub by Tommy-yw under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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