Graph Fourier transform for spatial omics representation and analyses of complex organs.

Autor:	Chang Y; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA.; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA., Liu J; School of Mathematics, Shandong University, Jinan 250100, China., Jiang Y; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA., Ma A; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA.; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA., Yeo YY; Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA., Guo Q; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA., McNutt M; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA., Krull J; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA.; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA., Rodig SJ; Department of Pathology, Dana Farber Cancer Institute, Boston, MA 02115 USA.; Department of Pathology, Brigham & Women's Hospital, Boston, MA 02115, USA., Barouch DH; Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA.; William Bosworth Castle Professor of Medicine, Harvard Medical School.; Ragon Institute of MGH, MIT, and Harvard., Nolan G; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA.; Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA., Xu D; Department of Electrical Engineering and Computer Science, and Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA., Jiang S; Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA.; Department of Pathology, Dana Farber Cancer Institute, Boston, MA 02115 USA.; Department of Pathology, Brigham & Women's Hospital, Boston, MA 02115, USA.; Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.; Department of Microbiology, Harvard Medical School, Boston, MA 02115, USA., Li Z; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA., Liu B; School of Mathematics, Shandong University, Jinan 250100, China., Ma Q; Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH 43210, USA.; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.
Jazyk:	angličtina
Zdroj:	Research square [Res Sq] 2024 Feb 15. Date of Electronic Publication: 2024 Feb 15.
DOI:	10.21203/rs.3.rs-3952048/v1
Abstrakt:	Spatial omics technologies are capable of deciphering detailed components of complex organs or tissue in cellular and subcellular resolution. A robust, interpretable, and unbiased representation method for spatial omics is necessary to illuminate novel investigations into biological functions, whereas a mathematical theory deficiency still exists. We present SpaGFT (Spatial Graph Fourier Transform), which provides a unique analytical feature representation of spatial omics data and elucidates molecular signatures linked to critical biological processes within tissues and cells. It outperformed existing tools in spatially variable gene prediction and gene expression imputation across human/mouse Visium data. Integrating SpaGFT representation into existing machine learning frameworks can enhance up to 40% accuracy of spatial domain identification, cell type annotation, cell-to-spot alignment, and subcellular hallmark inference. SpaGFT identified immunological regions for B cell maturation in human lymph node Visium data, characterized secondary follicle variations from in-house human tonsil CODEX data, and detected extremely rare subcellular organelles such as Cajal body and Set1/COMPASS. This new method lays the groundwork for a new theoretical model in explainable AI, advancing our understanding of tissue organization and function. Competing Interests: Additional Declarations: There is NO Competing Interest.
Databáze:	MEDLINE
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