GPTomics/bioskills
bioskills-installer/SKILL.md
Installs 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabilities or when a bioinformatics task requires specialized skills not yet installed.
$ install --global
skillsauthnpx skillsauth add GPTomics/bioSkills bioskillsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- bioskills
- description:
- Installs 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabilities or when a bioinformatics task requires specialized skills not yet installed.
- metadata:
- {"openclaw":{"requires":{"bins":["git"],"anyBins":["python3","Rscript"]},"os":["darwin","linux"],"emoji":"🧬"}}
bioSkills Installer
Meta-skill that installs the full bioSkills collection (425 skills across 62 categories) for bioinformatics analysis.
Installation
Run the bundled install script to download and install all bioSkills:
bash scripts/install-bioskills.sh
Or install only specific categories:
bash scripts/install-bioskills.sh --categories "single-cell,variant-calling,differential-expression"
What Gets Installed
425 skills across 62 categories covering:
- Sequence & Alignment (40): sequence-io, sequence-manipulation, alignment, alignment-files, database-access
- Read Processing (11): read-qc, read-alignment
- RNA-seq & Expression (14): differential-expression, rna-quantification, expression-matrix
- Single-Cell & Spatial (25): single-cell, spatial-transcriptomics
- Variant Analysis (21): variant-calling, copy-number, phasing-imputation
- Epigenomics (25): chip-seq, atac-seq, methylation-analysis, hi-c-analysis
- Metagenomics & Microbiome (13): metagenomics, microbiome
- Genomics & Assembly (29): genome-assembly, genome-annotation, genome-intervals, genome-engineering, primer-design
- Regulatory & Causal (13): gene-regulatory-networks, causal-genomics, rna-structure
- Temporal & Ecological (11): temporal-genomics, ecological-genomics
- Immunology & Clinical (25): immunoinformatics, clinical-databases, tcr-bcr-analysis, epidemiological-genomics
- Specialized Omics (36): proteomics, metabolomics, alternative-splicing, chemoinformatics, liquid-biopsy
- RNA Biology (20): small-rna-seq, epitranscriptomics, clip-seq, ribo-seq
- Phylogenetics & Evolution (16): phylogenetics, population-genetics, comparative-genomics
- Structural & Systems (11): structural-biology, systems-biology
- Screens & Cytometry (22): crispr-screens, flow-cytometry, imaging-mass-cytometry
- Pathway & Integration (14): pathway-analysis, multi-omics-integration, restriction-analysis
- Infrastructure (39): data-visualization, machine-learning, workflow-management, reporting, experimental-design, long-read-sequencing
- Workflows (40): end-to-end pipelines (FASTQ to results)
After Installation
Once installed, skills are automatically triggered based on the task at hand. Example requests:
- "I have RNA-seq counts from treated vs control samples - find the differentially expressed genes"
- "Call variants from this whole genome sequencing BAM file"
- "Cluster my single-cell RNA-seq data and find marker genes"
- "Predict the structure of this protein sequence"
- "Run a metagenomics classification on these shotgun reads"
Source
GitHub: https://github.com/GPTomics/bioSkills
Related Skills
GPTomics/bio-workflows-clip-pipeline
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End-to-end CLIP-seq pipeline from FASTQ to ENCODE-compliant binding sites, single-nucleotide crosslink maps, annotation, motifs, and (optionally) differential binding. Use when running the full Yeo lab eCLIP / iCLIP / iCLIP2 / iCLIP3 / irCLIP / PAR-CLIP analysis with SMInput control, protocol-specific UMI extraction, ENCODE STAR parameters, CLIPper or Skipper peak calling with stringent log2 FC and -log10 p thresholds, IDR rescue and self-consistency QC, and downstream motif registration with mCross or PEKA.
1,065SKILL.mdUpdated Jun 10, 2026
GPTomics/bio-comparative-genomics-whole-genome-duplication
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Detect, date, and contextualize whole-genome duplication (WGD / paleopolyploidy) events using wgd v2 (Chen et al 2024), KsRates (Sensalari 2022 substitution-rate-corrected Ks dating), DupGen_finder (Qiao 2019), MAPS (Li 2018 phylogenomic), POInT (Conant 2008 ordered-block), SLEDGe (2024 ML-based), Whale.jl (Bayesian DL+WGD), and synteny-anchored paranome construction. Use when identifying ancient polyploidy from Ks distributions and synteny block analysis, positioning WGD events relative to speciation, distinguishing tandem from segmental from WGD duplications, dating the 2R/3R vertebrate / fish / salmonid WGDs, building paranome and Ks-age mixture models, applying KsRates substitution-rate correction across lineages, or testing alternative biased-fractionation / dosage-balance models post-WGD.
1,065SKILL.mdUpdated May 23, 2026
GPTomics/bio-comparative-genomics-whole-genome-alignment
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Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.
1,065SKILL.mdUpdated May 23, 2026
GPTomics/bio-comparative-genomics-synteny-analysis
development
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Detect syntenic blocks and structural rearrangements between genomes using MCScanX (Wang 2012), JCVI/MCScan (Tang 2008 Python), GENESPACE (Lovell 2022) for orthology-anchored riparian visualization, SyRI for structural variation, AnchorWave for sequence-level synteny, i-ADHoRe 3.0 for highly diverged species, SynNet for synteny networks, and ntSynt for multi-genome macrosynteny. Use when identifying collinear gene blocks across species, distinguishing macrosynteny from microsynteny, detecting inversions/translocations/duplications, anchoring orthology in WGD lineages, producing publication riparian plots, computing synteny block age via Ks (cross-references whole-genome-duplication), or running synteny-aware ortholog inference in polyploids.
1,065SKILL.mdUpdated May 23, 2026