SpNeigh provides methods for neighborhood-aware analysis of spatial transcriptomics data. It supports boundary detection, spatial weighting (centroid- and boundary-based), spatially informed differential expression using spline-based models, and spatial enrichment analysis via the Spatial Enrichment Index (SEI). Designed for compatibility with Seurat objects, SpatialExperiment objects and spatial data frames, SpNeigh enables interpretable, publication-ready analysis of spatial gene expression patterns.
Quick start guide can be found here.
Install SpNeigh from Bioconductor
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("SpNeigh")Or install SpNeigh from GitHub:
devtools::install_github("jinming-cheng/SpNeigh")Please cite this article if you use SpNeigh:
To cite SpNeigh in publications, please use:
Cheng J, Chow P, Liu N (2026). "SpNeigh: spatial neighborhood and
differential expression analysis for high-resolution spatial
transcriptomics." _NAR Genomics and Bioinformatics_, *8*, lqag039.
doi:10.1093/nargab/lqag039 <https://doi.org/10.1093/nargab/lqag039>.
A BibTeX entry for LaTeX users is
@Article{,
title = {SpNeigh: spatial neighborhood and differential expression analysis for high-resolution spatial transcriptomics},
author = {Jinming Cheng and Pierce Kah Hoe Chow and Nan Liu},
journal = {NAR Genomics and Bioinformatics},
year = {2026},
volume = {8},
pages = {lqag039},
doi = {10.1093/nargab/lqag039},
}