scider: Spatial cell-type inter-correlation by density in R.

Overview

scider implements functions to analyse spatial transcriptomics data with cell type annotations by performing cell type correlation via density estimation and cell type co-localization via real number distance. Functions include density estimation, statistical modelling and visualizations.

Installation

Install the released version from Bioconductor:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("scider")

Install the development version from GitHub:

library(devtools)
devtools::install_github("ChenLaboratory/scider")

Case studies

Step-by-step case studies showing scider in action. Browse the full list under the Vignettes tab, or start here:

• Region based spatial transcriptomics analysis with scider: density estimation, region detection, and cell-type co-localization on a spatial dataset.

Citation

If you use scider in your work, please cite:

Li M, Liu N, Nguyen QH, Chen Y (2025). Preserving tissue structure through density-based spatial analysis with scider. bioRxiv. https://doi.org/10.1101/2025.09.11.675745