🧬 10x Genomics Spatial Transcriptomics

A comprehensive analysis of spatial transcriptomics data using Scanpy and Squidpy.

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📓 Notebooks With Full Results

Notebook	View Full Results
01 - Basic Scanpy Spatial Analysis	Open in Colab
02 - Visium Fluorescence Analysis	Open in Colab
03 - Visium H&E Analysis	Open in Colab
04 - Xenium Analysis	Code only (dataset requires 20GB+)

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📊 Notebook 01 — Basic Scanpy Spatial Analysis

Dataset: Visium Human Lymph Node

QC Distributions

UMAP Clusters

Spatial QC on Tissue

Spatial Clusters on H&E Image

Marker Genes

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📊 Notebook 02 — Visium Fluorescence Analysis

Dataset: Visium Mouse Brain (DAPI, anti-NEUN, anti-GFAP)

Spatial Clusters

Cell Segmentation

Image Feature Clusters

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📊 Notebook 03 — Visium H&E Analysis

Dataset: Visium Mouse Brain (H&E stained)

Spatial Clusters

Neighborhood Enrichment

Co-occurrence Score

Ligand-Receptor Interactions

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🗂️ Repository Structure

spatial-transcriptomics-10x/
├── README.md
├── environment/
│   ├── environment.yml
│   └── requirements.txt
├── notebooks/
│   ├── 01_scanpy_basic_spatial.ipynb
│   ├── 02_squidpy_visium_fluo.ipynb
│   ├── 03_squidpy_visium_hne.ipynb
│   └── 04_squidpy_xenium.ipynb
└── results/
    ├── 01_scanpy_basic_spatial_figures/
    ├── 02_squidpy_visium_fluo_figures/
    └── 03_squidpy_visium_hne_figures/

🚀 Setup

conda env create -f environment/environment.yml
conda activate spatial-genomics
jupyter lab

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📚 References

1. Wolf et al. (2018). SCANPY. Genome Biology.
2. Palla et al. (2022). Squidpy. Nature Methods.
3. Efremova et al. (2020). CellPhoneDB. Nature Protocols.

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👤 Author

Hamza Najeem — Bioinformatics Assignment, 2026