InSituCNV

This is a public repository to reproduce the analysis in the manusctipt In Situ Inference of Copy Number Variations in Image-Based Spatial Transcriptomics by Jensen et al., bioRxiv (2025), https://doi.org/10.1101/2025.07.02.662761.

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Code and Data Avaliability

These folders contains all R script and notebooks necessary to reproduce the analysis in this study. For simplicity, they are organized in the same order as they are presented in the manuscipt.

Figure 1

CosMx_CRC

Includes the analysis performed on the CosMx and snPATHO-seq datasets from colorectal tumor sample 221, avaliable in Crowell et al., "Tracing colorectal malignancy transformation from cell to tissue scale", bioRxiv (2025) https://doi.org/10.1101/2025.06.23.660674.

Xenium_prime_ovarian

Contains analysis of the publicly available high-grade ovarian cancer Xenium Prime dataset from 10x Genomics: https://www.10xgenomics.com/datasets/xenium-prime-fresh-frozen-human-ovary.

Xenium_prime_lymph_node

Contains analysis of the publicly available lymph node Xenium Prime dataset from 10x Genomics: https://www.10xgenomics.com/datasets/preview-data-xenium-prime-gene-expression.

Figure 2

This folder contains the code used to assess the technical limitations of CNV inference, as presented in Figure 2 of the manuscript "In Situ Inference of Copy Number Variations in Image-Based Spatial Transcriptomics". The 10x scRNA-seq dataset used for CNV simulation is available at: https://cellxgene.cziscience.com/collections/e9cf4e8d-05ed-4d95-b550-af35ca219390.

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How to use:

Clone the repository:

git clone https://github.com/Moldia/InSituCNV.git

Navigate to the directory:

cd InSituCNV

Create and activate a conda environment including all necessary dependencies:

conda env create --name insituCNV_env --file=insitucnv_env.yml

conda activate insituCNV_env