Qi Liu1,2, Chih-Yuan Hsu1,2 and Yu Shyr1,2 1Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA; 2Center for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA Corresponding authors: qi.liuvanderbilt.edu, yu.shyrvanderbilt.edu Abstract

The expeditious growth in spatial omics technologies enables the profiling of genome-wide molecular events at molecular and single-cell resolution, highlighting a need for fast and reliable methods to characterize spatial patterns. We developed SpaGene, a model-free method to discover spatial patterns rapidly in large-scale spatial omics studies. Analyzing simulation and a variety of spatially resolved transcriptomics data showed that SpaGene is more powerful and scalable than existing methods. Spatial expression patterns identified by SpaGene reconstruct unobserved tissue structures. SpaGene also successfully discovers ligand–receptor interactions through their colocalization.

Footnotes

[Supplemental material is available for this article.]

Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.276851.122.

Freely available online through the Genome Research Open Access option.

Received April 20, 2022. Accepted August 16, 2022.