# ST-prostate

**Repository Path**: shineboy/ST-prostate

## Basic Information

- **Project Name**: ST-prostate
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
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- **Created**: 2025-07-11
- **Last Updated**: 2025-07-11

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## README

### Single cell and spatial transcriptomics highlight the interaction of club-like cells with immunosuppressive myeloid cells in prostate cancer

[Link to the study](https://doi.org/10.1038/s41467-024-54364-1)

**Author:** Antti Kiviaho

**Email:** antti.kiviaho@tuni.fi

**Last modified:** 29.11.2024

This repository contains necessary code to reproduce results presented in the manuscript.

### Package versions:
- **single_cell_analysis_environment.yml** – Containts package versions used in the analysis of spatial transcriptomics data.
- **spatial_analysis_environment.yml** – Containts package versions used in the analysis of single-cell data.

## Spatial Transcriptomics data

Files related to ST data analysis

### Data preprocessing and computations

- **spatial-qc-and-normalization.ipynb** – Quality control and preprocessing of spatial transcriptomics data.

- **spatial-c2l-cell-type-reference-mapping.py** – Spatial transcriptomics data deconvolution using the cell type reference created from single-cell data.

- **spatial-post-c2l-cell-type-mapping.ipynb** – Division of spatial transcriptomics data into single-cell mapping-based (SCM) regions.

- **spatial-gene-set-scoring.py** – Gene set scoring on spatial data.

- **spatial-region-ligand-receptor-signaling-analysis.py** – Ligand-receptor interaction analysis.

- **spatial-to-pseudobulk.py** – Generating pseudobulk expression data from spatial transcriptomics data.

### Data analysis and plotting results

- **spatial-gene-expression-analysis.ipynb** – Gene expression analysis and plots of spatial transcriptomics data. (Figures 1c, 2d)

- **spatial-gene-set-score-analysis.ipynb** – Gene set scoring-based plotting (Figures 3a, 3b, 3c, 4a, 4b, 4c, 4d).

- **spatial-dotplot-ar-basal-club-markers.py** – Plot 2c generation.

- **spatial-dotplot-chemokine-expression.py** – Plot 3d generation.

- **multiplex_ihc_staining_analysis.ipynb** – Plots from mIHC cell classifier results (Figures 4h, 4i)

- **spatial-mapping-based-clusters-receptor-ligand-analyses.ipynb** – Ligand-receptor interaction analysis-based plotting (Supplementary Figure 8).

- **spatial-metastatic-tumor-sample-analysis.ipynb.ipynb** – Analysis of metastatic prostate cancer spatial transcriptomics samples (Figures 5d, 5e).

- **spatial-pseudobulk-data-analysis.ipynb** – Pseudobulk spatial transcriptomics data analysis and plots (Figures 5f, 5i).

- **public-sc-and-bulk-data-analysis.ipynb** – Analysis of public data He et al. 2021 + TCGA and SU2C gene expression data analyses (Figures 5a, 5b, 5g, 5h).

## Single-cell data analysis 

Files related to single-cell data used in the article

- **single-cell-preprocessing.ipynb** – Preprocessing of single-cell datasets to attain uniform format.

- **single-cell-quality-control.ipynb** – Gene filtering, doublet removal, and normalization steps carried out on each dataset individually.

- **single-cell-scvi-integrate.py** – scVI-based integration of 7 preprocessed single-cell datasets to find a common embedding.

- **single-cell-post-integration.ipynb** – Gene marker-based cell type annotation on the integrated dataset. Removal of sample-specfic clusters.

- **single-cell-nmf-analysis.py** – Non-negative matrix factorization-based annotation of cell type-specific gene expression modules.

- **single-cell-immune-celltypist.ipynb** – Celltypist-based annotation of cells annotated as immune cells on the previous round (broad annotation).

- **single-cell-gene-module-based-annotation.ipynb** – Non-immune cell subtype annotation based on the NMF gene expression modules.

- **single-cell-generate-c2l-celltype-reference.py** – Annotation-based regression of cell2location-compatible cell type signatures.