visium-hd

Ecotypes of Triple-Negative Breast Cancer in Response to Chemotherapy

Optimized pipelines for Spatial Transcriptomics (ST) data analysis using Seurat & Giotto, designed for reproducible benchmarking and biological insight.

Identifying cell-type-specific spatially variable genes

A python toolkit for spatial domains and spatially variable genes discovery for high-resolution spatially resolved transcriptomics data.

A visual analytics system for spatiotemporal exploration of spatial transcriptomics data, designed to support multi-resolution analysis and cross-sample comparison

Step-by-step QC workflow for Visium HD nuclear segmentation on Windows (WSL2) using spaceranger segment and QuPath

📐 Cylindrical Bessel K0 biophysical transport solver for perivascular tumour cords & pharmacological sanctuary sleeves.

Spatial-sequencing: The final frontier. These are the voyages of the 10x Visium pipeline, space-seek.

🔬 10x Visium HD 2 µm subcellular spatial atlas uncovering perivascular transport limits (λ ≈ 624 µm) in EGFR-mutant NSCLC.

This pipeline applies SpotSweeper in a full spatial transcriptomic pipeline divided into 14 sections

Spatial Transcriptome

single-cell RNA-seq, spatial transcriptomics, and spatial proteomics analysis skills

Hands-on R tutorials for single-cell and spatial transcriptomics (Seurat, Visium, RCTD, ISCHIA, Visium HD) with a ready-to-run RStudio Docker image. Spatial Biology of Cancer course, ETH Zurich 2026.

Identify cell-density correlated genes in spatial transcriptomics with a Bayesian marked point process (R and Python)

A R package for deconvolving low‐resolution Visium HD spatial data back to high‐resolution spots via barcode‐ and coordinate‐based methods, with built‐in visualization.

🔬 Benchmark Spatial Transcriptomics data analysis with optimized pipelines using Seurat and Giotto for reproducible results and biological insights.

BioWorkbench