LEGEND: Identifying Co-expressed Genes in Multimodal Transcriptomic Sequencing Data.

ABSTRACT: Identifying co-expressed genes across tissue domains and cell types is essential for revealing co-functional genes involved in biological or pathological processes. While both single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) data offer insights into gene co-expression patterns, current methods typically utilize either data type alone, potentially diluting the co-functionality signals within co-expressed gene groups. To bridge this gap, we introduce muLtimodal co-Expressed GENes finDer (LEGEND), a novel computational method that integrates scRNA-seq and SRT data for identifying groups of co-expressed genes at both cell type and tissue domain levels. LEGEND employs an innovative hierarchical clustering algorithm designed to maximize intra-cluster redundancy

SUBMITTER: Deng T 

PROVIDER: S-EPMC12715406 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature