Abstract

Spatial transcriptomics (ST) has the potential to provide unprecedented insights into gene expression across tissue architecture, but existing analytical methods often overlook the full complexity of the spatial dimension. We present STExplorer, an R package that adapts well-established computational geography (CG) methods to explore the micro-geography of spatial omics data. By incorporating techniques like Geographically Weighted Principal Component Analysis (GWPCA), Fuzzy Geographically Weighted Clustering (FGWC), Geographically Weighted Regression (GWR), and analyses of observation Spatial Autocorrelation (SA), STExplorer enables the uncovering of spatially resolved patterns that capture the spatial heterogeneity of biological data. STExplorer provides a complete suite of functions for spatial analyses and visualisations, supporting deeper biological understanding and inference. Built on the Bioconductor ecosystem, the package integrates with SpatialFeatureExperiment objects, ensuring compatibility with existing pipelines. It includes preprocessing capabilities such as data import, quality control, gene count normalisation, and variable gene selection, alongside tools for downstream analysis and detailed visualisations that quantify and map spatial heterogeneity and relationships. We demonstrate the utility of STExplorer through applications to spatial transcriptomics datasets, revealing that spatially varying gene expression and relationships are often masked by standard analyses. By bridging bioinformatics and CG, STExplorer provides a novel and informed approach to spatial transcriptomics analysis, with robust tools to address spatial heterogeneity and its associated underlying biology, thereby advancing our understanding of complex tissue biology without reinventing the wheel.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

* Page margins changed so bioRxiv header does not overlap text; no alterations to content.

* https://github.com/LefterisZ/STExplorer

* https://github.com/ncl-icbam/STExplorer_Analysis

Details

Title
STExplorer: Navigating the Micro-Geography of Spatial Omics Data
Author
Zormpas, Eleftherios; Vlachogiannis, Nikolaos I; Resteu, Anastasia; Unsworth, Adrienne; Simon Tual-Chalot; Dorgau, Birthe; Queen, Rachel; Lako, Majlinda; Tiniakos, Dina; Comber, Alexis; Anstee, Quentin M; Giakountis, Antonis; Cockell, Simon J
University/institution
Cold Spring Harbor Laboratory Press
Section
New Results
Publication year
2025
Publication date
Jan 23, 2025
Publisher
Cold Spring Harbor Laboratory Press
ISSN
2692-8205
Source type
Working Paper
Language of publication
English
ProQuest document ID
3158241612
Copyright
© 2025. This article is published under http://creativecommons.org/licenses/by/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.