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Smoother: a unified and modular framework for incorporating structural dependency in spatial omics data.
Su, Jiayu; Reynier, Jean-Baptiste; Fu, Xi; Zhong, Guojie; Jiang, Jiahao; Escalante, Rydberg Supo; Wang, Yiping; Aparicio, Luis; Izar, Benjamin; Knowles, David A; Rabadan, Raul.
Afiliación
  • Su J; Program for Mathematical Genomics, Columbia University, New York, NY, USA. js5756@cumc.columbia.edu.
  • Reynier JB; Department of Systems Biology, Columbia University, New York, NY, USA. js5756@cumc.columbia.edu.
  • Fu X; New York Genome Center, New York, NY, USA. js5756@cumc.columbia.edu.
  • Zhong G; Program for Mathematical Genomics, Columbia University, New York, NY, USA.
  • Jiang J; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Escalante RS; Program for Mathematical Genomics, Columbia University, New York, NY, USA.
  • Wang Y; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Aparicio L; Department of Systems Biology, Columbia University, New York, NY, USA.
  • Izar B; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
  • Knowles DA; Department of Systems Biology, Columbia University, New York, NY, USA.
  • Rabadan R; Program for Mathematical Genomics, Columbia University, New York, NY, USA.
Genome Biol ; 24(1): 291, 2023 12 18.
Article en En | MEDLINE | ID: mdl-38110959
ABSTRACT
Spatial omics technologies can help identify spatially organized biological processes, but existing computational approaches often overlook structural dependencies in the data. Here, we introduce Smoother, a unified framework that integrates positional information into non-spatial models via modular priors and losses. In simulated and real datasets, Smoother enables accurate data imputation, cell-type deconvolution, and dimensionality reduction with remarkable efficiency. In colorectal cancer, Smoother-guided deconvolution reveals plasma cell and fibroblast subtype localizations linked to tumor microenvironment restructuring. Additionally, joint modeling of spatial and single-cell human prostate data with Smoother allows for spatial mapping of reference populations with significantly reduced ambiguity.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Próstata / Fibroblastos Límite: Humans / Male Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Próstata / Fibroblastos Límite: Humans / Male Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido