Research on the Algorithm for Identifying Spatial Expression Pattern Genes Based on the Kernel Function
WANG Lin
ZHAO Guihua
Abstract：Spatial transcriptomics is a mature technique for analyzing histological changes in tissues with complex gene expres-sion.Identifying genes,that display spatial expression patterns,is an important first step in characterizing the spatial transcriptomic landscape of complex tissues.In this paper,the kernel function of the statistical method SPARK is modified to identify the spatial ex-pression patterns of genes in the data generated by various spatially resolved transcriptomic techniques.Two sets of simulated data are given,the SPARK2 method produces higher power than existing methods,such as low false positives and high true positives.In addition,by analyzing three published spatially resolved transcriptomic datasets,the SPARK2 approach is found to be more power-ful than existing methods,such as identifying more SE(spatial expression)genes and revealing more biological findings.Therefore,improving the kernel function can increase the number of genes identified with spatial expression patterns,while also identifying genes of biological significance.
Keywords：gene expression patternsGauss kernelperiodic kernel
Publication Date：2025-11-20
Online Publishing Date：2026-01-28(First online date of this platform, not the publication date of the document)
Pages：6( 3027-3031,3038 )