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Spatial transcriptomics analysis

Skill bg-szy/TOP-SKILLS/skills/awesome-skills/spatial-transcriptomics-analysis

Automated analysis pipeline for Spatial Transcriptomics (Visium, Xenium) integrating histology and gene expression.From its SKILL.md

Install
npx -y skills add bg-szy/TOP-SKILLS --skill spatial-transcriptomics-analysis

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SKILL.md

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<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

Spatial Transcriptomics Skill

Version: 1.0.0 Author: MD BABU MIA, PhD Date: February 2026

Overview

This skill provides automated analysis capabilities for Spatial Transcriptomics data, specifically designed for 10x Visium and Xenium platforms. It enables the integration of histological data with gene expression profiles to uncover spatial organization of cell types.

Capabilities

  1. Data Loading: Supports Spaceranger output (h5, images).
  2. QC & Preprocessing: Spatial QC metrics, normalization.
  3. Spatial Variable Features: Identification of spatially variable genes (SVGs) using Moran's I and Geary's C.
  4. Deconvolution: Interface for cell type deconvolution (mapping scRNA-seq to spatial).
  5. Visualization: Interactive spatial plots overlaying gene expression on tissue images.

Usage

from Skills.Genomics.Spatial_Transcriptomics.spatial_analyzer import SpatialAnalyzer

# Initialize
sa = SpatialAnalyzer(data_path="./data/visium_sample1")

# Run Pipeline
sa.load_data()
sa.preprocess()
sa.find_spatial_features()
sa.plot_spatial("INS", save_path="./output/insulin_spatial.png")

Requirements

  • scanpy
  • squidpy
  • anndata
  • matplotlib
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it: 1 file

3.0 KB alongside SKILL.md, 1 of them executable

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