Research skills

Browse reusable Agent Skills, each with a clear purpose and practical guidance.

single-cell-downstream-analysis

Checklist-style reference for OmicVerse downstream tutorials covering AUCell scoring, metacell DEG, and related exports.

2.85k repo starsObserved in 14 repos
Research

single-cell-preprocessing-with-omicverse

Walk through omicverse's single-cell preprocessing tutorials to QC PBMC3k data, normalise counts, detect HVGs, and run PCA/embedding pipelines on CPU, CPU–GPU mixed, or GPU stacks.

2.85k repo starsObserved in 14 repos
Research

single-trajectory-analysis

Guide to reproducing OmicVerse trajectory workflows spanning PAGA, Palantir, VIA, velocity coupling, and fate scoring notebooks.

2.85k repo starsObserved in 14 repos
Research

tooluniverse-expression-data-retrieval

Retrieves gene expression and omics datasets from ArrayExpress and BioStudies with gene disambiguation, experiment quality assessment, and structured reports. Creates comprehensive dataset profiles with metadata, sample information, and download links. Use when users need expression data, omics datasets, or mention ArrayExpress (E-MTAB, E-GEOD) or BioStudies (S-BSST) accessions.

2.85k repo starsObserved in 14 repos
Research

tooluniverse-metabolomics

Comprehensive metabolomics research skill for identifying metabolites, analyzing studies, and searching metabolomics databases. Integrates HMDB (220k+ metabolites), MetaboLights, Metabolomics Workbench, and PubChem. Use when asked to identify or annotate metabolites (HMDB IDs, chemical properties, pathways), retrieve metabolomics study information from MetaboLights (MTBLS*) or Metabolomics Workbench (ST*), search for studies by keywords or disease, or generate comprehensive metabolomics research reports.

2.85k repo starsObserved in 14 repos
Research

tooluniverse-single-cell

Production-ready single-cell and expression matrix analysis using scanpy, anndata, and scipy. Performs scRNA-seq QC, normalization, PCA, UMAP, Leiden/Louvain clustering, differential expression (Wilcoxon, t-test, DESeq2), cell type annotation, per-cell-type statistical analysis, gene-expression correlation, batch correction (Harmony), trajectory inference, and cell-cell communication analysis. NEW: Analyzes ligand-receptor interactions between cell types using OmniPath (CellPhoneDB, CellChatDB), scores communication strength, identifies signaling cascades, and handles multi-subunit receptor complexes. Integrates with ToolUniverse gene annotation tools (HPA, Ensembl, MyGene, UniProt) and enrichment tools (gseapy, PANTHER, STRING). Supports h5ad, 10X, CSV/TSV count matrices, and pre-annotated datasets. Use when analyzing single-cell RNA-seq data, studying cell-cell interactions, performing cell type differential expression, computing gene-expression correlations by cell type, analyzing tumor-immune communication, or answering questions about scRNA-seq datasets.

2.85k repo starsObserved in 14 repos
Research

tooluniverse-spatial-omics-analysis

Computational analysis framework for spatial multi-omics data integration. Given spatially variable genes (SVGs), spatial domain annotations, tissue type, and disease context from spatial transcriptomics/proteomics experiments (10x Visium, MERFISH, DBiTplus, SLIDE-seq, etc.), performs comprehensive biological interpretation including pathway enrichment, cell-cell interaction inference, druggable target identification, immune microenvironment characterization, and multi-modal integration. Produces a detailed markdown report with Spatial Omics Integration Score (0-100), domain-by-domain characterization, and validation recommendations. Uses 70+ ToolUniverse tools across 9 analysis phases. Use when users ask about spatial transcriptomics analysis, spatial omics interpretation, tissue heterogeneity, spatial gene expression patterns, tumor microenvironment mapping, tissue zonation, or cell-cell communication from spatial data.

2.85k repo starsObserved in 14 repos
Research

tooluniverse-spatial-transcriptomics

Analyze spatial transcriptomics data to map gene expression in tissue architecture. Supports 10x Visium, MERFISH, seqFISH, Slide-seq, and imaging-based platforms. Performs spatial clustering, domain identification, cell-cell proximity analysis, spatial gene expression patterns, tissue architecture mapping, and integration with single-cell data. Use when analyzing spatial transcriptomics datasets, studying tissue organization, identifying spatial expression patterns, mapping cell-cell interactions in tissue context, characterizing tumor microenvironment spatial structure, or integrating spatial and single-cell RNA-seq data for comprehensive tissue analysis.

2.85k repo starsObserved in 14 repos
Research

tooluniverse-statistical-modeling

Perform statistical modeling and regression analysis on biomedical datasets. Supports linear regression, logistic regression (binary/ordinal/multinomial), mixed-effects models, Cox proportional hazards survival analysis, Kaplan-Meier estimation, and comprehensive model diagnostics. Extracts odds ratios, hazard ratios, confidence intervals, p-values, and effect sizes. Designed to solve BixBench statistical reasoning questions involving clinical/experimental data. Use when asked to fit regression models, compute odds ratios, perform survival analysis, run statistical tests, or interpret model coefficients from provided data.

2.85k repo starsObserved in 14 repos
Research