{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,13]],"date-time":"2026-11-13T21:37:23Z","timestamp":1794605843715,"version":"4.9.1"},"reference-count":77,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T00:00:00Z","timestamp":1724889600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T00:00:00Z","timestamp":1724889600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Commun"],"DOI":"10.1038\/s41467-024-51590-5","type":"journal-article","created":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T00:02:09Z","timestamp":1724889729000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Graph Fourier transform for spatial omics representation and analyses of complex organs"],"prefix":"10.1038","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4893-1886","authenticated-orcid":false,"given":"Yuzhou","family":"Chang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jixin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6269-398X","authenticated-orcid":false,"given":"Anjun","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7604-2296","authenticated-orcid":false,"given":"Yao Yu","family":"Yeo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Megan","family":"McNutt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6507-8085","authenticated-orcid":false,"given":"Jordan E.","family":"Krull","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott J.","family":"Rodig","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5127-4659","authenticated-orcid":false,"given":"Dan H.","family":"Barouch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8862-9043","authenticated-orcid":false,"given":"Garry P.","family":"Nolan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4809-0514","authenticated-orcid":false,"given":"Dong","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6149-3142","authenticated-orcid":false,"given":"Sizun","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4603-927X","authenticated-orcid":false,"given":"Zihai","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5734-1135","authenticated-orcid":false,"given":"Bingqiang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3264-8392","authenticated-orcid":false,"given":"Qin","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,8,29]]},"reference":[{"key":"51590_CR1","doi-asserted-by":"publisher","first-page":"1940","DOI":"10.1016\/j.immuni.2022.09.002","volume":"55","author":"S Liu","year":"2022","unstructured":"Liu, S. et al. Spatial maps of T cell receptors and transcriptomes reveal distinct immune niches and interactions in the adaptive immune response. Immunity 55, 1940\u20131952.e1945 (2022).","journal-title":"Immunity"},{"key":"51590_CR2","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1038\/s41576-023-00580-2","volume":"24","author":"K Vandereyken","year":"2023","unstructured":"Vandereyken, K., Sifrim, A., Thienpont, B. & Voet, T. Methods and applications for single-cell and spatial multi-omics. Nat. Rev. Genet. 24, 494\u2013515 (2023).","journal-title":"Nat. Rev. Genet."},{"key":"51590_CR3","doi-asserted-by":"publisher","first-page":"1089","DOI":"10.1038\/s41556-023-01194-w","volume":"25","author":"S Jain","year":"2023","unstructured":"Jain, S. et al. Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP). Nat. Cell Biol. 25, 1089\u20131100 (2023).","journal-title":"Nat. Cell Biol."},{"key":"51590_CR4","doi-asserted-by":"crossref","unstructured":"Hu, J. et al. SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network. Nat. Methods 18, 1342\u20131351 (2021).","DOI":"10.1038\/s41592-021-01255-8"},{"key":"51590_CR5","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1016\/j.cell.2020.07.005","volume":"182","author":"CM Sch\u00fcrch","year":"2020","unstructured":"Sch\u00fcrch, C. M. et al. Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front. Cell 182, 1341\u20131359.e1319 (2020).","journal-title":"Cell"},{"key":"51590_CR6","doi-asserted-by":"crossref","unstructured":"Mages, S. et al. TACCO unifies annotation transfer and decomposition of cell identities for single-cell and spatial omics. Nat. Biotechnol. 41, 1465\u20131473 (2023).","DOI":"10.1038\/s41587-023-01657-3"},{"key":"51590_CR7","doi-asserted-by":"publisher","first-page":"1352","DOI":"10.1038\/s41592-021-01264-7","volume":"18","author":"T Biancalani","year":"2021","unstructured":"Biancalani, T. et al. Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram. Nat. Methods 18, 1352\u20131362 (2021).","journal-title":"Nat. Methods"},{"key":"51590_CR8","doi-asserted-by":"publisher","first-page":"950","DOI":"10.1038\/s41592-022-01560-w","volume":"19","author":"Y Wang","year":"2022","unstructured":"Wang, Y. et al. Sprod for de-noising spatially resolved transcriptomics data based on position and image information. Nat. Methods 19, 950\u2013958 (2022).","journal-title":"Nat. Methods"},{"key":"51590_CR9","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1038\/s41592-019-0701-7","volume":"17","author":"S Sun","year":"2020","unstructured":"Sun, S., Zhu, J. & Zhou, X. Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies. Nat. Methods 17, 193\u2013200 (2020).","journal-title":"Nat. Methods"},{"key":"51590_CR10","doi-asserted-by":"publisher","first-page":"1665","DOI":"10.1016\/j.cell.2020.10.026","volume":"183","author":"Y Liu","year":"2020","unstructured":"Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665\u20131681.e1618 (2020).","journal-title":"Cell"},{"key":"51590_CR11","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1038\/nmeth.4636","volume":"15","author":"V Svensson","year":"2018","unstructured":"Svensson, V., Teichmann, S. A. & Stegle, O. SpatialDE: identification of spatially variable genes. Nat. Methods 15, 343\u2013346 (2018).","journal-title":"Nat. Methods"},{"key":"51590_CR12","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-021-02404-0","volume":"22","author":"J Zhu","year":"2021","unstructured":"Zhu, J., Sun, S. & Zhou, X. SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies. Genome Biol. 22, 184 (2021).","journal-title":"Genome Biol."},{"key":"51590_CR13","doi-asserted-by":"publisher","first-page":"1462","DOI":"10.1038\/s41592-023-01992-y","volume":"20","author":"B Velten","year":"2023","unstructured":"Velten, B. & Stegle, O. Principles and challenges of modeling temporal and spatial omics data. Nat. Methods 20, 1462\u20131474 (2023).","journal-title":"Nat. Methods"},{"key":"51590_CR14","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1038\/s41586-023-05769-3","volume":"619","author":"BB Lake","year":"2023","unstructured":"Lake, B. B. et al. An atlas of healthy and injured cell states and niches in the human kidney. Nature 619, 585\u2013594 (2023).","journal-title":"Nature"},{"key":"51590_CR15","doi-asserted-by":"publisher","first-page":"e15","DOI":"10.1017\/ATSIP.2020.13","volume":"9","author":"F Chen","year":"2020","unstructured":"Chen, F., Wang, Y.-C., Wang, B. & Kuo, C.-C. J. Graph representation learning: a survey. APSIPA Trans. Signal Inf. Process. 9, e15 (2020).","journal-title":"APSIPA Trans. Signal Inf. Process."},{"key":"51590_CR16","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1038\/s41592-023-01894-z","volume":"20","author":"H Spitzer","year":"2023","unstructured":"Spitzer, H., Berry, S., Donoghoe, M., Pelkmans, L. & Theis, F. J. Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps. Nat. Methods 20, 1058\u20131069 (2023).","journal-title":"Nat. Methods"},{"key":"51590_CR17","doi-asserted-by":"publisher","DOI":"10.1126\/science.aar7042","volume":"361","author":"G Gut","year":"2018","unstructured":"Gut, G., Herrmann, M. D. & Pelkmans, L. Multiplexed protein maps link subcellular organization to cellular states. Science 361, eaar7042 (2018).","journal-title":"Science"},{"key":"51590_CR18","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1016\/j.crhy.2019.08.003","volume":"20","author":"B Ricaud","year":"2019","unstructured":"Ricaud, B., Borgnat, P., Tremblay, N., Gon\u00e7alves, P. & Vandergheynst, P. Fourier could be a data scientist: from graph Fourier transform to signal processing on graphs. C. R. Phys. 20, 474\u2013488 (2019).","journal-title":"C. R. Phys."},{"key":"51590_CR19","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1109\/MSP.2012.2235192","volume":"30","author":"DI Shuman","year":"2013","unstructured":"Shuman, D. I., Narang, S. K., Frossard, P., Ortega, A. & Vandergheynst, P. The emerging field of signal processing on graphs: extending high-dimensional data analysis to networks and other irregular domains. IEEE Signal Process. Mag. 30, 83\u201398 (2013).","journal-title":"IEEE Signal Process. Mag."},{"key":"51590_CR20","doi-asserted-by":"crossref","unstructured":"Palla, G., Fischer, D. S., Regev, A. & Theis, F. J. Spatial components of molecular tissue biology. Nat. Biotechnol. 40, 308\u2013318 (2022).","DOI":"10.1038\/s41587-021-01182-1"},{"key":"51590_CR21","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1016\/j.freeradbiomed.2021.11.011","volume":"179","author":"RM Buzzi","year":"2022","unstructured":"Buzzi, R. M. et al. Spatial transcriptome analysis defines heme as a hemopexin-targetable inflammatoxin in the brain. Free Radic. Biol. Med. 179, 277\u2013287 (2022).","journal-title":"Free Radic. Biol. Med."},{"key":"51590_CR22","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1038\/s41587-020-0739-1","volume":"39","author":"RR Stickels","year":"2021","unstructured":"Stickels, R. R. et al. Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Nat. Biotechnol. 39, 313\u2013319 (2021).","journal-title":"Nat. Biotechnol."},{"key":"51590_CR23","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1186\/s40478-022-01494-6","volume":"10","author":"S Chen","year":"2022","unstructured":"Chen, S. et al. Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer\u2019s disease. Acta Neuropathol. Commun. 10, 188 (2022).","journal-title":"Acta Neuropathol. Commun."},{"key":"51590_CR24","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1038\/s41593-020-00787-0","volume":"24","author":"KR Maynard","year":"2021","unstructured":"Maynard, K. R. et al. Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex. Nat. Neurosci. 24, 425\u2013436 (2021).","journal-title":"Nat. Neurosci."},{"key":"51590_CR25","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abb3446","volume":"6","author":"C Ortiz","year":"2020","unstructured":"Ortiz, C. et al. Molecular atlas of the adult mouse brain. Sci. Adv. 6, eabb3446 (2020).","journal-title":"Sci. Adv."},{"key":"51590_CR26","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1038\/s41586-019-1506-7","volume":"573","author":"RD Hodge","year":"2019","unstructured":"Hodge, R. D. et al. Conserved cell types with divergent features in human versus mouse cortex. Nature 573, 61\u201368 (2019).","journal-title":"Nature"},{"key":"51590_CR27","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1038\/s41586-018-0654-5","volume":"563","author":"B Tasic","year":"2018","unstructured":"Tasic, B. et al. Shared and distinct transcriptomic cell types across neocortical areas. Nature 563, 72\u201378 (2018).","journal-title":"Nature"},{"key":"51590_CR28","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1038\/nn.4216","volume":"19","author":"B Tasic","year":"2016","unstructured":"Tasic, B. et al. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat. Neurosci. 19, 335\u2013346 (2016).","journal-title":"Nat. Neurosci."},{"key":"51590_CR29","unstructured":"Science, A.I.f.B. Allen Institute for Brain Science (2004). Allen Mouse Brain Atlas [dataset] (Allen Institute for Brain Science, 2011)."},{"key":"51590_CR30","doi-asserted-by":"crossref","unstructured":"Miller, B. F., Bambah-Mukku, D., Dulac, C., Zhuang, X. & Fan, J. Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities. Genome Res. gr. 271288.271120 (2021).","DOI":"10.1101\/gr.271288.120"},{"key":"51590_CR31","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-33182-3","volume":"13","author":"K Zhang","year":"2022","unstructured":"Zhang, K., Feng, W. & Wang, P. Identification of spatially variable genes with graph cuts. Nat. Commun. 13, 5488 (2022).","journal-title":"Nat. Commun."},{"key":"51590_CR32","doi-asserted-by":"publisher","first-page":"808","DOI":"10.1109\/JPROC.2018.2820126","volume":"106","author":"A Ortega","year":"2018","unstructured":"Ortega, A., Frossard, P., Kova\u010devi\u0107, J., Moura, J. M. F. & Vandergheynst, P. Graph signal processing: overview, challenges, and applications. Proc. IEEE 106, 808\u2013828 (2018).","journal-title":"Proc. IEEE"},{"key":"51590_CR33","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-020-02132-x","volume":"21","author":"W Hou","year":"2020","unstructured":"Hou, W., Ji, Z., Ji, H. & Hicks, S. C. A systematic evaluation of single-cell RNA-sequencing imputation methods. Genome Biol. 21, 218 (2020).","journal-title":"Genome Biol."},{"key":"51590_CR34","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1101\/gr.251603.119","volume":"30","author":"R Elyanow","year":"2020","unstructured":"Elyanow, R., Dumitrascu, B., Engelhardt, B. E. & Raphael, B. J. netNMF-sc: leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysis. Genome Res. 30, 195\u2013204 (2020).","journal-title":"Genome Res."},{"key":"51590_CR35","doi-asserted-by":"crossref","unstructured":"Kleshchevnikov, V. et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nat. Biotechnol. 40, 661\u2013671 (2022).","DOI":"10.1038\/s41587-021-01139-4"},{"key":"51590_CR36","doi-asserted-by":"crossref","unstructured":"Li, B. et al. Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution. Nat. Methods 19, 662\u2013670 (2022).","DOI":"10.1038\/s41592-022-01480-9"},{"key":"51590_CR37","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.cels.2021.09.012","volume":"13","author":"SS Bhate","year":"2022","unstructured":"Bhate, S. S., Barlow, G. L., Sch\u00fcrch, C. M. & Nolan, G. P. Tissue schematics map the specialization of immune tissue motifs and their appropriation by tumors. Cell Syst. 13, 109\u2013130.e106 (2022).","journal-title":"Cell Syst."},{"key":"51590_CR38","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1016\/j.immuni.2011.03.024","volume":"34","author":"SM Kerfoot","year":"2011","unstructured":"Kerfoot, S. M. et al. Germinal center B cell and T follicular helper cell development initiates in the interfollicular zone. Immunity 34, 947\u2013960 (2011).","journal-title":"Immunity"},{"key":"51590_CR39","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1182\/asheducation-2007.1.210","volume":"2007","author":"Y Natkunam","year":"2007","unstructured":"Natkunam, Y. The biology of the germinal center. Hematology 2007, 210\u2013215 (2007).","journal-title":"Hematology"},{"key":"51590_CR40","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1038\/s41587-021-01094-0","volume":"40","author":"NF Greenwald","year":"2022","unstructured":"Greenwald, N. F. et al. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nat. Biotechnol. 40, 555\u2013565 (2022).","journal-title":"Nat. Biotechnol."},{"key":"51590_CR41","doi-asserted-by":"publisher","first-page":"636","DOI":"10.1002\/cyto.a.22625","volume":"87","author":"S Van Gassen","year":"2015","unstructured":"Van Gassen, S. et al. FlowSOM: using self-organizing maps for visualization and interpretation of cytometry data. Cytometry Part A 87, 636\u2013645 (2015).","journal-title":"Cytometry Part A"},{"key":"51590_CR42","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1038\/nmeth.4149","volume":"14","author":"KE Diggins","year":"2017","unstructured":"Diggins, K. E., Greenplate, A. R., Leelatian, N., Wogsland, C. E. & Irish, J. M. Characterizing cell subsets using marker enrichment modeling. Nat. Methods 14, 275\u2013278 (2017).","journal-title":"Nat. Methods"},{"key":"51590_CR43","doi-asserted-by":"crossref","unstructured":"Liu, C.C. et al. Robust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering. Nat Commun. 14, 4618 (2023).","DOI":"10.1038\/s41467-023-40068-5"},{"key":"51590_CR44","doi-asserted-by":"publisher","first-page":"1494","DOI":"10.3324\/haematol.2019.243543","volume":"105","author":"G Pavlasova","year":"2020","unstructured":"Pavlasova, G. & Mraz, M. The regulation and function of CD20: an \u201cenigma\u201d of B-cell biology and targeted therapy. Haematologica 105, 1494\u20131506 (2020).","journal-title":"Haematologica"},{"key":"51590_CR45","doi-asserted-by":"crossref","unstructured":"Meda, B. A. et al. BCL-2 Is consistently expressed in hyperplastic marginal zones of the spleen, abdominal lymph nodes, and ileal lymphoid tissue. Am. J. Surg. Pathol. 27, 888\u2013894 (2003).","DOI":"10.1097\/00000478-200307000-00003"},{"key":"51590_CR46","doi-asserted-by":"publisher","first-page":"6961","DOI":"10.1073\/pnas.88.16.6961","volume":"88","author":"DM Hockenbery","year":"1991","unstructured":"Hockenbery, D. M., Zutter, M., Hickey, W., Nahm, M. & Korsmeyer, S. J. BCL2 protein is topographically restricted in tissues characterized by apoptotic cell death. Proc. Natl Acad. Sci. USA 88, 6961\u20136965 (1991).","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"51590_CR47","doi-asserted-by":"publisher","first-page":"2139","DOI":"10.1084\/jem.20161794","volume":"214","author":"A Heit","year":"2017","unstructured":"Heit, A. et al. Vaccination establishes clonal relatives of germinal center T cells in the blood of humans. J. Exp. Med. 214, 2139\u20132152 (2017).","journal-title":"J. Exp. Med."},{"key":"51590_CR48","doi-asserted-by":"publisher","first-page":"68","DOI":"10.4049\/jimmunol.173.1.68","volume":"173","author":"T Chtanova","year":"2004","unstructured":"Chtanova, T. et al. T follicular helper cells express a distinctive transcriptional profile, reflecting their role as non-Th1\/Th2 effector cells that provide help for B cells1. J. Immunol. 173, 68\u201378 (2004).","journal-title":"J. Immunol."},{"key":"51590_CR49","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1097\/01.pas.0000209855.28282.ce","volume":"30","author":"DM Dorfman","year":"2006","unstructured":"Dorfman, D. M., Brown, J. A., Shahsafaei, A. & Freeman, G. J. Programmed death-1 (PD-1) is a marker of germinal center-associated T cells and angioimmunoblastic T-cell lymphoma. Am. J. Surg. Pathol. 30, 802\u2013810 (2006).","journal-title":"Am. J. Surg. Pathol."},{"key":"51590_CR50","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1097\/PAI.0b013e318183a8e2","volume":"17","author":"DK Marsee","year":"2009","unstructured":"Marsee, D. K., Pinkus, G. S. & Hornick, J. L. Podoplanin (D2-40) is a highly effective marker of follicular dendritic cells. Appl. Immunohistochem. Mol. Morphol. 17, 102\u2013107 (2009).","journal-title":"Appl. Immunohistochem. Mol. Morphol."},{"key":"51590_CR51","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1159\/000337007","volume":"4","author":"EE Gray","year":"2012","unstructured":"Gray, E. E. & Cyster, J. G. Lymph node macrophages. J. Innate Immun. 4, 424\u2013436 (2012).","journal-title":"J. Innate Immun."},{"key":"51590_CR52","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.4049\/jimmunol.171.4.1657","volume":"171","author":"B Johansson-Lindbom","year":"2003","unstructured":"Johansson-Lindbom, B., Ingvarsson, S. & Borrebaeck, C. A. Germinal centers regulate human Th2 development. J. Immunol. 171, 1657\u20131666 (2003).","journal-title":"J. Immunol."},{"key":"51590_CR53","doi-asserted-by":"crossref","unstructured":"Nakagawa, R. & Calado, D. P. Positive selection in the light zone of germinal centers. Front. Immunol. 12, 661678 (2021).","DOI":"10.3389\/fimmu.2021.661678"},{"key":"51590_CR54","doi-asserted-by":"publisher","first-page":"943","DOI":"10.1038\/ni1100","volume":"5","author":"CDC Allen","year":"2004","unstructured":"Allen, C. D. C. et al. Germinal center dark and light zone organization is mediated by CXCR4 and CXCR5. Nat. Immunol. 5, 943\u2013952 (2004).","journal-title":"Nat. Immunol."},{"key":"51590_CR55","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1016\/j.immuni.2007.07.009","volume":"27","author":"CD Allen","year":"2007","unstructured":"Allen, C. D., Okada, T. & Cyster, J. G. Germinal-center organization and cellular dynamics. Immunity 27, 190\u2013202 (2007).","journal-title":"Immunity"},{"key":"51590_CR56","doi-asserted-by":"crossref","unstructured":"Wang, X. et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science 361, eaat5691 (2018).","DOI":"10.1126\/science.aat5691"},{"key":"51590_CR57","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1038\/s41592-018-0254-1","volume":"16","author":"M B\u00fcttner","year":"2019","unstructured":"B\u00fcttner, M., Miao, Z., Wolf, F. A., Teichmann, S. A. & Theis, F. J. A test metric for assessing single-cell RNA-seq batch correction. Nat. methods 16, 43\u201349 (2019).","journal-title":"Nat. methods"},{"key":"51590_CR58","doi-asserted-by":"publisher","first-page":"2108","DOI":"10.1016\/j.bbamcr.2008.07.016","volume":"1783","author":"GE Morris","year":"2008","unstructured":"Morris, G. E. The Cajal body. Biochim. Biophys. Acta (BBA) - Mol. Cell Res. 1783, 2108\u20132115 (2008).","journal-title":"Biochim. Biophys. Acta (BBA) - Mol. Cell Res."},{"key":"51590_CR59","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-10786-w","volume":"10","author":"K Tajima","year":"2019","unstructured":"Tajima, K. et al. SETD1A protects from senescence through regulation of the mitotic gene expression program. Nat. Commun. 10, 2854 (2019).","journal-title":"Nat. Commun."},{"key":"51590_CR60","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-43256-5","volume":"14","author":"J Wang","year":"2023","unstructured":"Wang, J. et al. Dimension-agnostic and granularity-based spatially variable gene identification using BSP. Nat. Commun. 14, 7367 (2023).","journal-title":"Nat. Commun."},{"key":"51590_CR61","doi-asserted-by":"publisher","unstructured":"Li, Z. et al. Benchmarking computational methods to identify spatially variable genes and peaks. Preprint at bioRxiv https:\/\/doi.org\/10.1101\/2023.12.02.569717 (2023).","DOI":"10.1101\/2023.12.02.569717"},{"key":"51590_CR62","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-023-37477-x","volume":"14","author":"X Tang","year":"2023","unstructured":"Tang, X. et al. Explainable multi-task learning for multi-modality biological data analysis. Nat. Commun. 14, 2546 (2023).","journal-title":"Nat. Commun."},{"key":"51590_CR63","doi-asserted-by":"crossref","unstructured":"Bao, F. et al. Integrative spatial analysis of cell morphologies and transcriptional states with MUSE. Nat. Biotechnol. 40, 1200\u20131209 (2022).","DOI":"10.1038\/s41587-022-01251-z"},{"key":"51590_CR64","doi-asserted-by":"crossref","unstructured":"Chang, Y. et al. Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning. Comput Struct Biotechnol J. 20, 4600\u20134617 (2022).","DOI":"10.1016\/j.csbj.2022.08.029"},{"key":"51590_CR65","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1109\/JSTSP.2016.2600859","volume":"10","author":"W Huang","year":"2016","unstructured":"Huang, W. et al. Graph frequency analysis of brain signals. IEEE J. Sel. Top. Signal Process. 10, 1189\u20131203 (2016).","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"51590_CR66","doi-asserted-by":"publisher","first-page":"4855","DOI":"10.1109\/TSP.2019.2932882","volume":"67","author":"K-S Lu","year":"2019","unstructured":"Lu, K.-S. & Ortega, A. Fast graph Fourier transforms based on graph symmetry and bipartition. IEEE Trans. Signal Process. 67, 4855\u20134869 (2019).","journal-title":"IEEE Trans. Signal Process."},{"key":"51590_CR67","first-page":"407","volume":"4","author":"LL Magoarou","year":"2018","unstructured":"Magoarou, L. L., Gribonval, R. & Tremblay, N. Approximate fast graph Fourier transforms via multilayer sparse approximations. IEEE Trans. Signal Inf. Process. Netw. 4, 407\u2013420 (2018).","journal-title":"IEEE Trans. Signal Inf. Process. Netw."},{"key":"51590_CR68","doi-asserted-by":"crossref","unstructured":"Satopaa, V., Albrecht, J., Irwin, D. & Raghavan, B. Finding a \u2018kneedle\u2019 in a haystack: detecting knee points in system behavior. In Proc. 2011 31st International Conference on Distributed Computing Systems Workshops (ed. Du) 166\u2013171 (IEEE, 2011).","DOI":"10.1109\/ICDCSW.2011.20"},{"key":"51590_CR69","doi-asserted-by":"publisher","first-page":"2815","DOI":"10.1038\/s41596-022-00738-y","volume":"17","author":"J Lu","year":"2022","unstructured":"Lu, J. et al. Metagenome analysis using the Kraken software suite. Nat. Protoc. 17, 2815\u20132839 (2022).","journal-title":"Nat. Protoc."},{"key":"51590_CR70","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.687673","volume":"12","author":"D Phillips","year":"2021","unstructured":"Phillips, D. et al. Highly multiplexed phenotyping of immunoregulatory proteins in the tumor microenvironment by CODEX tissue imaging. Front. Immunol. 12, 687673 (2021).","journal-title":"Front. Immunol."},{"key":"51590_CR71","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"W Zhou","year":"2004","unstructured":"Zhou, W., Bovik, A. C., Sheikh, H. R. & Simoncelli, E. P. Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13, 600\u2013612 (2004).","journal-title":"IEEE Trans. Image Process."},{"key":"51590_CR72","doi-asserted-by":"publisher","first-page":"1118","DOI":"10.1016\/j.immuni.2022.03.020","volume":"55","author":"S Jiang","year":"2022","unstructured":"Jiang, S. et al. Combined protein and nucleic acid imaging reveals virus-dependent B cell and macrophage immunosuppression of tissue microenvironments. Immunity 55, 1118\u20131134.e1118 (2022).","journal-title":"Immunity"},{"key":"51590_CR73","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1126\/science.abm1741","volume":"377","author":"R Fang","year":"2022","unstructured":"Fang, R. et al. Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH. Science 377, 56\u201362 (2022).","journal-title":"Science"},{"key":"51590_CR74","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1007\/s10444-013-9323-2","volume":"40","author":"B Ricaud","year":"2014","unstructured":"Ricaud, B. & Torr\u00e9sani, B. A survey of uncertainty principles and some signal processing applications. Adv. Comput. Math. 40, 629\u2013650 (2014).","journal-title":"Adv. Comput. Math."},{"key":"51590_CR75","unstructured":"Rybkin, O., Daniilidis, K. & Levine, S. Simple and effective VAE training with calibrated decoders. In Proc. International Conference on Machine Learning (ed. Meila) 9179\u20139189 (PMLR, 2021)."},{"key":"51590_CR76","doi-asserted-by":"publisher","first-page":"1563","DOI":"10.1038\/s41591-023-02327-2","volume":"29","author":"L Sikkema","year":"2023","unstructured":"Sikkema, L. et al. An integrated cell atlas of the lung in health and disease. Nat. Med. 29, 1563\u20131577 (2023).","journal-title":"Nat. Med."},{"key":"51590_CR77","unstructured":"Liu, J. et al. SpaGFT Github: OSU-BMBL\/SpaGFT: 0.1.1. Zenodo (2024)."}],"container-title":["Nature Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41467-024-51590-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41467-024-51590-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41467-024-51590-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T01:03:28Z","timestamp":1724893408000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41467-024-51590-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,29]]},"references-count":77,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["51590"],"URL":"https:\/\/doi.org\/10.1038\/s41467-024-51590-5","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-3952048\/v1","asserted-by":"object"}]},"ISSN":["2041-1723"],"issn-type":[{"value":"2041-1723","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,29]]},"assertion":[{"value":"12 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 August 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 August 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"S.J. is a co-founder of Elucidate Bio Inc., has received speaking honorariums from Cell Signaling Technology, and has received research support from Roche unrelated to this work. The other authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"7467"}}