Faculty, Staff and Student Publications
Language
English
Publication Date
7-1-2025
Journal
Nature Communications
DOI
10.1038/s41467-025-61142-0
PMID
40595621
PMCID
PMC12217155
PubMedCentral® Posted Date
7-1-2025
PubMedCentral® Full Text Version
Post-print
Abstract
Multi-modal spatial omics data are invaluable for exploring complex cellular behaviors in diseases from both morphological and molecular perspectives. Current analytical methods primarily focus on clustering and classification, and do not adequately examine the relationship between cell morphology and molecular dynamics. Here, we present MorphLink, a framework designed to systematically identify disease-related morphological-molecular interplays. MorphLink has been evaluated across a wide array of datasets, showcasing its effectiveness in extracting and linking interpretable morphological features with various molecular measurements in spatial omics analyses. These linkages provide a transparent view of cellular behavior heterogeneity within tissue regions with similar cell type compositions, characterizing tumor subtypes and immune diversity across different organs. Additionally, MorphLink is scalable and robust against cross-sample batch effects, making it an efficient method for integrative spatial omics data analysis across samples, cohorts, and modalities, and enhancing the interpretation of results for large-scale studies.
Keywords
Humans, Neoplasms, Computational Biology, Computational models, Image processing, Statistical methods, Transcriptomics
Published Open-Access
yes
Recommended Citation
Huang, Jing; Yuan, Chenyang; Jiang, Jiahui; et al., "Bridging Cell Morphological Behaviors and Molecular Dynamics in Multi-modal Spatial Omics With MorphLink" (2025). Faculty, Staff and Student Publications. 5694.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/5694
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons