Scanpy

Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations.

FreedomIntelligence/OpenClaw-Medical-Skills

Walks through single-cell RNA-seq analysis with Scanpy: loading .h5ad and 10X data, QC, normalization, PCA and UMAP, Leiden clustering, marker genes and cell type annotation.

davila7/claude-code-templates

Reproducible Scanpy workflow for human or mouse 10x scRNA-seq and snRNA-seq count matrices: single-sample descriptive QC, clustering and annotation, or comparative donor-aware pseudobulk DE and Milo…

PKU-YuanGroup/OpenAI4S

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling…

davila7/claude-code-templates

Query CZ CELLxGENE Census (61M+ cells). An agent skill from davila7/claude-code-templates.

davila7/claude-code-templates

Prepares bulk RNA-seq FASTQ, Salmon, STAR or featureCounts output for gene-level differential expression.

K-Dense-AI/scientific-agent-skills

Performs pathway and gene-set enrichment analysis on gene lists or ranked gene data and interprets the results.

K-Dense-AI/scientific-agent-skills

Performs RNA velocity analysis with scVelo from spliced and unspliced single-cell RNA counts.

K-Dense-AI/scientific-agent-skills

Performs Scanpy single-cell RNA-seq QC, normalization, HVG selection, PCA/UMAP/t-SNE, clustering, exploratory marker ranking, pseudobulk preparation, visualization, and Seurat or…

K-Dense-AI/scientific-agent-skills

Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data.

K-Dense-AI/scientific-agent-skills

Fits probabilistic models for single-cell omics, including scVI batch integration, scANVI annotation, totalVI CITE-seq, MultiVI RNA/ATAC integration, and posterior differential expression.

K-Dense-AI/scientific-agent-skills

Omics and single-cell workflow guide for AnnData, Scanpy-style dataset profiling, PyDESeq2-oriented count checks, pysam alignment inspection, and pyOpenMS mass-spectrometry summaries.

DrugClaw/DrugClaw

Probabilistic single-cell RNA-seq with scvi-tools — scVI for a batch-corrected latent space, scANVI for semi-supervised label transfer, and Bayesian differential expression.

JimLiu/science-skills

Handles annotated matrices in single-cell analysis, .h5ad and Zarr files, and integration with the scverse ecosystem.

K-Dense-AI/scientific-agent-skills

Annotated matrices for single-cell genomics. An agent skill from jaechang-hits/SciAgent-Skills.

jaechang-hits/SciAgent-Skills

Local Scanpy pipeline for single-cell RNA-seq QC, optional doublet detection, clustering, marker discovery, optional CellTypist annotation, optional latent downstream mode from…

ClawBio/ClawBio

Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions)…

GPTomics/bioSkills

Read, write, and create single-cell data objects using Seurat (R) and Scanpy (Python).

FreedomIntelligence/OpenClaw-Medical-Skills

Quality control, filtering, and normalization for single-cell RNA-seq using Seurat (R) and Scanpy (Python).

FreedomIntelligence/OpenClaw-Medical-Skills

Load spatial transcriptomics data from Visium, Xenium, MERFISH, Slide-seq, and other platforms using Squidpy and SpatialData.

FreedomIntelligence/OpenClaw-Medical-Skills

Dimensionality reduction and clustering for single-cell RNA-seq using Seurat (R) and Scanpy (Python).

FreedomIntelligence/OpenClaw-Medical-Skills

Find marker genes and annotate cell types in single-cell RNA-seq using Seurat (R) and Scanpy (Python).

FreedomIntelligence/OpenClaw-Medical-Skills

Analyze multi-modal single-cell data (CITE-seq, Multiome, spatial).

FreedomIntelligence/OpenClaw-Medical-Skills

Identify spatial domains and tissue regions in spatial transcriptomics data using Squidpy and Scanpy.

FreedomIntelligence/OpenClaw-Medical-Skills

Quality control, filtering, normalization, and feature selection for spatial transcriptomics data.

FreedomIntelligence/OpenClaw-Medical-Skills

Visualize spatial transcriptomics data using Squidpy and Scanpy.

FreedomIntelligence/OpenClaw-Medical-Skills

Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces.

GPTomics/bioSkills

Dimensionality reduction and graph-based clustering for single-cell RNA-seq with Scanpy (Python) and Seurat (R).

GPTomics/bioSkills

Detect cluster marker genes and assign manual cell type labels in single-cell RNA-seq using Scanpy (Python) and Seurat (R).

GPTomics/bioSkills

Quality control, ambient-RNA handling, normalization, and feature selection for single-cell RNA-seq using Scanpy (Python) and Seurat (R).

GPTomics/bioSkills

Quality control, filtering, and normalization for spatial transcriptomics (Visium, Visium HD, Xenium, MERFISH/MERSCOPE, CosMx, Slide-seq) with Squidpy and Scanpy.

GPTomics/bioSkills

Plots spatial transcriptomics expression, clusters, and annotations on tissue using Squidpy and Scanpy.

GPTomics/bioSkills

Orchestrates the end-to-end spatial transcriptomics pipeline from Space Ranger / vendor output to spatial domains and statistics, branching FIRST on platform class (imaging in-situ…

GPTomics/bioSkills

RNA velocity analysis with scVelo. An agent skill from lamm-mit/scienceclaw.

lamm-mit/scienceclaw

Open-source FAIR biology data framework. An agent skill from jaechang-hits/SciAgent-Skills.

jaechang-hits/SciAgent-Skills

Primary retained Python toolkit for molecular biology sequence work.

foryourhealth111-pixel/Vibe-Skills

Standard single-cell RNA-seq analysis pipeline. An agent skill from aipoch/medical-research-skills.

aipoch/medical-research-skills

Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML.

GPTomics/bioSkills

Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <- CSR (Python) implicit…

GPTomics/bioSkills

scRNA-seq with Scanpy: QC, normalization, HVG selection, PCA, neighborhood graph, UMAP/t-SNE, Leiden clustering, markers, cell annotation, trajectory inference.

jaechang-hits/SciAgent-Skills

Machine learning toolkit for genomic interval (BED) data; use it when you need to tokenize BED collections and train embeddings for regions/cells/labels, build consensus peak universes, or run…

aipoch/medical-research-skills

Harmony batch correction for scRNA-seq and other omics. An agent skill from jaechang-hits/SciAgent-Skills.

jaechang-hits/SciAgent-Skills

Multi-modal single-cell analysis with muon/MuData. An agent skill from jaechang-hits/SciAgent-Skills.

jaechang-hits/SciAgent-Skills

Load when finding marker genes per cluster or comparing condition expression in single-cell RNA-seq.

TianGzlab/OmicsClaw

Load when ranking cluster-level marker genes from a clustered single-cell AnnData via Scanpy Wilcoxon / t-test / logreg or COSG specificity.

TianGzlab/OmicsClaw

Load when computing per-cell pathway / gene-set scores on a normalised scRNA AnnData via AUCell (R or Python) or Scanpy scoregenes.

TianGzlab/OmicsClaw

Load when normalising QC'd scRNA into a PCA-ready AnnData via scanpy / Seurat / SCTransform / Pearson residuals.

TianGzlab/OmicsClaw

Local Scanpy pipeline for single-cell RNA-seq QC, clustering, marker discovery, and optional two-group differential expression from raw-count .h5ad.

FreedomIntelligence/OpenClaw-Medical-Skills