Data & Analytics

Compute HEIM diversity and equity metrics from VCF or ancestry data. Generates heterozygosity, FST, PCA plots, and a composite HEIM Equity Score with markdown reports.

--> --- name: 'epigenomics-methylgpt-agent' description: 'AI-powered DNA methylation analysis using MethylGPT foundation models for epigenomic profiling, differential methylation detection, and cancer epigenome characterization.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Epigenomics MethylGPT Agent** leverages foundation models for comprehensive DNA methylation analysis. It integrates M...

--> --- name: 'digital-twin-clinical-agent' description: 'AI-powered patient digital twin creation for clinical trial simulation, treatment outcome prediction, and personalized medicine using real-world data and multi-omics integration.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Digital Twin Clinical Agent** creates AI-powered virtual replicas of individual patients by integrating genom...

Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.

--> --- name: data-visualization-expert description: Generate insightful, publication-quality visualizations from complex datasets. keywords: - charts - plots - analysis - pandas - matplotlib - seaborn measurable_outcome: Create 3 high-resolution (300dpi) statistical plots (volcano, heatmap, scatter) within 15 minutes. license: MIT metadata: author: AI Agentic Skills Team version: "2.0.0" compatibility: - system: linux, macos allowed-tools: - run_shell_command - write_file - read_file --- A d...

Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.

--> --- name: 'ctdna-dynamics-mrd-agent' description: 'AI-powered circulating tumor DNA dynamics analysis for molecular residual disease detection, treatment response monitoring, and early relapse prediction using liquid biopsy.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **ctDNA Dynamics MRD Agent** provides comprehensive analysis of circulating tumor DNA dynamics for molecular residual d...

Shotgun metagenomics profiling — taxonomy, resistome, and functional pathways

Ancestry decomposition PCA against the Simons Genome Diversity Project

Assist Claude in running PyWGCNA through omicverse—preprocessing expression matrices, constructing co-expression modules, visualising eigengenes, and extracting hub genes.

Guide Claude through omicverse's bulk RNA-seq DEG pipeline, from gene ID mapping and DESeq2 normalization to statistical testing, visualization, and pathway enrichment. Use when a user has bulk count matrices and needs differential expression analysis in omicverse.

--> --- name: biomedical-data-analysis description: Omics data forge keywords: - pandas - R-tidyverse - SQL - visualization - reproducible measurable_outcome: Deliver a cleaned dataset + statistical summary + at least one visualization or dashboard spec for each request within 1 working session (≤30 minutes). license: MIT metadata: author: BioSkills Team version: "1.0.0" compatibility: - system: Python 3.9+ / R 4.0+ allowed-tools: - run_shell_command - read_file - python_repl --- Run the cros...

--> --- name: bio-workflows-spatial-pipeline description: End-to-end spatial transcriptomics workflow for Visium/Xenium data. Covers data loading, preprocessing, spatial analysis, domain detection, and visualization with Squidpy. Use when analyzing spatial transcriptomics data. tool_type: python primary_tool: Squidpy workflow: true depends_on: - spatial-transcriptomics/spatial-data-io - spatial-transcriptomics/spatial-preprocessing - spatial-transcriptomics/spatial-neighbors - spatial-transcr...

--> --- name: bio-workflows-rnaseq-to-de description: End-to-end RNA-seq workflow from FASTQ files to differential expression results. Covers QC, quantification (Salmon or STAR+featureCounts), and DESeq2 analysis with visualization. Use when running RNA-seq from FASTQ to DE results. tool_type: mixed primary_tool: DESeq2 workflow: true depends_on: - read-qc/fastp-workflow - rna-quantification/alignment-free-quant - rna-quantification/tximport-workflow - differential-expression/deseq2-basics - ...

--> --- name: bio-workflows-proteomics-pipeline description: End-to-end proteomics workflow from MaxQuant output to differential protein abundance. Orchestrates data import, normalization, imputation, and statistical testing with MSstats or limma. Use when processing mass spectrometry proteomics. tool_type: mixed primary_tool: MSstats workflow: true depends_on: - proteomics/data-import - proteomics/proteomics-qc - proteomics/quantification - proteomics/protein-inference - proteomics/different...

--> --- name: bio-workflows-microbiome-pipeline description: End-to-end 16S amplicon workflow from FASTQ reads to differential abundance. Orchestrates DADA2 ASV inference, taxonomy assignment, diversity analysis, and compositional testing with ALDEx2. Use when processing 16S/ITS amplicon data. tool_type: r primary_tool: dada2 workflow: true depends_on: - microbiome/amplicon-processing - microbiome/taxonomy-assignment - microbiome/diversity-analysis - microbiome/differential-abundance measurab...

--> --- name: bio-workflows-metabolomics-pipeline description: End-to-end metabolomics workflow from raw MS data to pathway analysis. Orchestrates XCMS preprocessing, annotation, normalization, statistical analysis, and pathway mapping. Use when processing LC-MS metabolomics data. tool_type: r primary_tool: XCMS workflow: true depends_on: - metabolomics/xcms-preprocessing - metabolomics/metabolite-annotation - metabolomics/normalization-qc - metabolomics/statistical-analysis - metabolomics/pa...

--> --- name: bio-workflows-imc-pipeline description: End-to-end imaging mass cytometry workflow from raw acquisitions to spatial cell analysis. Orchestrates image preprocessing, segmentation, phenotyping, and spatial statistics. Use when analyzing imaging mass cytometry data end-to-end. tool_type: python primary_tool: steinbock workflow: true depends_on: - imaging-mass-cytometry/data-preprocessing - imaging-mass-cytometry/cell-segmentation - imaging-mass-cytometry/phenotyping - imaging-mass-...

--> --- name: bio-workflows-hic-pipeline description: End-to-end Hi-C analysis workflow from contact pairs to compartments, TADs, and loops. Covers cooler matrices, cooltools analysis, and visualization. Use when processing Hi-C data to compartments and TADs. tool_type: mixed primary_tool: cooler workflow: true depends_on: - hi-c-analysis/hic-data-io - hi-c-analysis/contact-pairs - hi-c-analysis/matrix-operations - hi-c-analysis/compartment-analysis - hi-c-analysis/tad-detection - hi-c-analys...

--> --- name: bio-workflows-gwas-pipeline description: End-to-end GWAS workflow from VCF to association results. Covers PLINK QC, population structure correction, and association testing for case-control or quantitative traits. Use when running genome-wide association studies. tool_type: mixed primary_tool: PLINK2 workflow: true depends_on: - population-genetics/plink-basics - population-genetics/population-structure - population-genetics/association-testing - population-genetics/linkage-dise...

--> --- name: bio-workflows-cytometry-pipeline description: End-to-end flow cytometry workflow from FCS files to differential analysis. Orchestrates compensation, transformation, gating/clustering, and statistical testing with CATALYST/diffcyt. Use when processing flow or mass cytometry data end-to-end. tool_type: r primary_tool: CATALYST workflow: true depends_on: - flow-cytometry/fcs-handling - flow-cytometry/compensation-transformation - flow-cytometry/gating-analysis - flow-cytometry/clus...

--> --- name: bio-workflows-crispr-screen-pipeline description: End-to-end CRISPR screen analysis from FASTQ to hit genes. Orchestrates guide counting, QC, statistical analysis with MAGeCK, and hit calling with multiple methods. Use when analyzing pooled CRISPR screens from count data to hit calling. tool_type: mixed primary_tool: MAGeCK workflow: true depends_on: - crispr-screens/screen-qc - crispr-screens/mageck-analysis - crispr-screens/hit-calling - crispr-screens/library-design - crispr-...

--> --- name: bio-workflows-biomarker-pipeline description: End-to-end biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, classifier training with nested CV, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data. tool_type: python primary_tool: sklearn workflow: true depends_on: - machine-learning/biomarker-discovery - machine-learning/model-validation - ...