SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes

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• dc.contributor.author Elosua-Bayés, Marc
• dc.contributor.author Nieto, Paula
• dc.contributor.author Mereu, Elisabetta
• dc.contributor.author Gut, Ivo Glynne
• dc.contributor.author Heyn, Holger
• dc.date.accessioned 2021-03-23T11:10:46Z
• dc.date.available 2021-03-23T11:10:46Z
• dc.date.issued 2021
• dc.description.abstract Spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots). Simulating varying reference quantities and qualities, we confirmed high prediction accuracy also with shallowly sequenced or small-sized scRNA-seq reference datasets. SPOTlight deconvolution of the mouse brain correctly mapped subtle neuronal cell states of the cortical layers and the defined architecture of the hippocampus. In human pancreatic cancer, we successfully segmented patient sections and further fine-mapped normal and neoplastic cell states. Trained on an external single-cell pancreatic tumor references, we further charted the localization of clinical-relevant and tumor-specific immune cell states, an illustrative example of its flexible application spectrum and future potential in digital pathology.
• dc.description.sponsorship Funding: Ministerio de Ciencia, Innovación y Universidades [SAF2017-89109-P, AEI/FEDER to U.E.]; project (BCLLATLAS) that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme [810287]; Chan Zuckerberg Initiative (in part); Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme/Generalitat de Catalunya; Spanish Ministry of Science and Innovation through the Instituto de Salud Carlos III, the Generalitat de Catalunya through Departament de Salut and Departament d’Empresa i Coneixement; Spanish Ministry of Science and Innovation with funds from the European Regional Development Fund (ERDF) corresponding to the 2014–2020 Smart Growth Operating Program. Funding for open access charge: Ministerio de Ciencia, Innovación y Universidades [SAF2017-89109-P, AEI/FEDER to U.E.]
• dc.format.mimetype application/pdf
• dc.identifier.citation Elosua-Bayes M, Nieto P, Mereu E, Gut I, Heyn H. SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes. Nucleic Acids Res. 2021;49(9):e50. DOI: 10.1093/nar/gkab043
• dc.identifier.doi http://dx.doi.org/10.1093/nar/gkab043
• dc.identifier.issn 0305-1048
• dc.identifier.uri http://hdl.handle.net/10230/46906
• dc.language.iso eng
• dc.publisher Oxford University Press
• dc.relation.ispartof Nucleic Acids Research. 2021;49(9):e50
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/810287
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/SAF2017-89109-P
• dc.rights © Marc Elosua-Bayes et al 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
• dc.subject.other Genètica
• dc.subject.other Expressió gènica
• dc.subject.other Pàncrees -- Càncer
• dc.title SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion