This repository contains code for processing, analysis, and visualization of Xenium spatial transcriptomics data associated with the manuscript An interorgan neuroimmune circuit promotes visceral hypersensitivity (Wang et al., Nature, 2026). We identify and spatially map neuron subsets within the L6 dorsal root ganglion (DRG). Using probes specific to AAV-induced EGFP and dTomato transcripts, we detect colon- and bladder- innervating neurons, respectively, enabling transcriptomic characterization of these organ-specific sensory neurons.
Raw spatial transcriptomics data generated using Xenium In Situ technology are available at GEO under accession number: GSE316300.
Single-cell RNA-seq reference datasets:
- GSE139088 - DRG scRNA-seq (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE139088)
- GSE254789 - DRG scRNA-seq (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE254789)
All notebooks are organized in numbered order. Before running, configure file paths in config/paths.py and config/paths.R to match your computing environment.
| Subdirectory | Description |
|---|---|
00a_download-xenium |
Download and organize raw Xenium output data from external sources |
00b_download_references |
Process and prepare single-cell RNA-seq reference datasets (GSE139088, GSE254789) |
01_pre-processing |
QC filtering, normalization, and scVI integration of Xenium data |
02_cell-labels |
Cell type annotation using reference mapping (ScanVI and Seurat) |
03_neurons |
Subclustering and refinement of neuronal populations |
04_thresholds |
Determine reporter expression thresholds using Gaussian mixture models |
05_figures |
Data visualization and figure generation |
06_geo |
Prepare and format data for GEO submission |
Conda environment specifications are provided in the envs/ directory. Each notebook specifies its required environment at the top.
Analyses were developed by @mncowan and @kathleenabadie.