Lecuit, T. & Lenne, P.-F. Cell surface mechanics and the control of cell shape, tissue patterns and morphogenesis. Nat. Rev. Mol. Cell Biol. 8, 633–644 (2007).

Article  CAS  PubMed  Google Scholar 

Zeller, R., López-Ríos, J. & Zuniga, A. Vertebrate limb bud development: moving towards integrative analysis of organogenesis. Nat. Rev. Genet. 10, 845–858 (2009).

Article  CAS  PubMed  Google Scholar 

Egeblad, M., Nakasone, E. S. & Werb, Z. Tumors as organs: complex tissues that interface with the entire organism. Dev. Cell 18, 884–901 (2010).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Takeichi, M. Dynamic contacts: rearranging adherens junctions to drive epithelial remodelling. Nat. Rev. Mol. Cell Biol. 15, 397–410 (2014).

Article  CAS  PubMed  Google Scholar 

Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).

Article  CAS  PubMed  Google Scholar 

Hanahan, D. Hallmarks of cancer: new dimensions. Cancer Discov. 12, 31–46 (2022).

Article  CAS  PubMed  Google Scholar 

Stark, R., Grzelak, M. & Hadfield, J. RNA sequencing: the teenage years. Nat. Rev. Genet. 20, 631–656 (2019).

Article  CAS  PubMed  Google Scholar 

Ståhl, P. L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78–82 (2016).

Article  PubMed  Google Scholar 

Moses, L., Pachter, L. Museum of spatial transcriptomics. Nat Methods 19, 534–546 (2022). This Review introduces spatial transcriptomics technologies and its core concepts and tools for data analysis.

Article  CAS  PubMed  Google Scholar 

Tian, L., Chen, F. & Macosko, E. Z. The expanding vistas of spatial transcriptomics. Nat Biotechnol 41, 773–782 (2023).

Article  CAS  PubMed  Google Scholar 

Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681.e18 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Merritt, C. R. et al. Multiplex digital spatial profiling of proteins and RNA in fixed tissue. Nat. Biotechnol. 38, 586–599 (2020).

Article  CAS  PubMed  Google Scholar 

Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with harmony. Nat. Methods 16, 1289–1296 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Welch, J. D. et al. Single-cell multi-omic integration compares and contrasts features of brain cell identity. Cell 177, 1873–1887.e17 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen, B., Khodadoust, M. S., Liu, C. L., Newman, A. M. & Alizadeh, A. A. Profiling tumor infiltrating immune cells with CIBERSORT. Methods Mol. Biol. 1711, 243–259 (2018).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Avila Cobos, F., Alquicira-Hernandez, J., Powell, J. E., Mestdagh, P. & De Preter, K. Benchmarking of cell type deconvolution pipelines for transcriptomics data. Nat. Commun. 11, 5650 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang, Y. et al. Deconvolution algorithms for inference of the cell-type composition of the spatial transcriptome. Comput. Struct. Biotechnol. J. 21, 176–184 (2023).

Article  CAS  PubMed  Google Scholar 

Longo, S. K., Guo, M. G., Ji, A. L. & Khavari, P. A. Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics. Nat. Rev. Genet. 22, 627–644 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Garmire, L. X. et al. Challenges and perspectives in computational deconvolution of genomics data. Nat. Methods 21, 391–400 (2024).

Article  CAS  PubMed  Google Scholar 

Gaujoux, R. & Seoighe, C. CellMix: a comprehensive toolbox for gene expression deconvolution. Bioinformatics 29, 2211–2212 (2013).

Article  CAS  PubMed  Google Scholar 

Newman, A. M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang, X., Park, J., Susztak, K., Zhang, N. R. & Li, M. Bulk tissue cell type deconvolution with multi-subject single-cell expression reference. Nat. Commun. 10, 380 (2019).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Tsoucas, D. et al. Accurate estimation of cell-type composition from gene expression data. Nat. Commun. 10, 2975 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Dong, R. & Yuan, G.-C. SpatialDWLS: accurate deconvolution of spatial transcriptomic data. Genome Biol. 22, 145 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Xun, Z. et al. Reconstruction of the tumor spatial microenvironment along the malignant–boundary–nonmalignant axis. Nat. Commun. 14, 933 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yang, T. et al. AdRoit is an accurate and robust method to infer complex transcriptome composition. Commun. Biol. 4, 1–14 (2021).

Article  Google Scholar 

Chen, Y., Ruan, F. & Wang, J.-P. NLSDeconv: an efficient cell-type deconvolution method for spatial transcriptomics data. Bioinformatics 41, btae747 (2024).

Article  PubMed  PubMed Central  Google Scholar 

Zhou, Z., Zhong, Y., Zhang, Z. & Ren, X. Spatial transcriptomics deconvolution at single-cell resolution using Redeconve. Nat. Commun. 14, 7930 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

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. 49, e50 (2021). This study showcases one of the first deconvolution methods for spatial transcriptomics data, SPOTlight, which combines matrix factorization with non-negative least squares regression to perform cell-type deconvolution.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ru, B., Huang, J., Zhang, Y., Aldape, K. & Jiang, P. Estimation of cell lineages in tumors from spatial transcriptomics data. Nat. Commun. 14, 568 (2023).

Article