References

[AL21]

Alma Anderson and Joakim Lundeberg. Sepal: identifying transcript profiles with spatial patterns by diffusion-based modeling. Bioinformatics, 2021. doi:10.1093/bioinformatics/btab164.

[BRT15]

Adrian Baddeley, Ege Rubak, and Rolf Turner. Spatial Point Patterns: Methodology and Applications with R. CRC Press, November 2015.

[EVTTVT20]

Mirjana Efremova, Miquel Vento-Tormo, Sarah A Teichmann, and Roser Vento-Tormo. Cellphonedb: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes. Nature protocols, 15(4):1484–1506, 2020. doi:10.1038/s41596-020-0292-x.

[GHP18]

Gabriele Gut, Markus D Herrmann, and Lucas Pelkmans. Multiplexed protein maps link subcellular organization to cellular states. Science, 2018. doi:10.1126/science.aar7042.

[HSS08]

Aric A. Hagberg, Daniel A. Schult, and Pieter J. Swart. Exploring network structure, dynamics, and function using networkx. In Gaël Varoquaux, Travis Vaught, and Jarrod Millman, editors, Proceedings of the 7th Python in Science Conference, 11 – 15. Pasadena, CA USA, 2008.

[HMM+20]

Felix J. Hartmann, Dunja Mrdjen, Erin McCaffrey, David R. Glass, Noah F. Greenwald, Anusha Bharadwaj, Zumana Khair, Alex Baranski, Reema Baskar, Michael Angelo, and Sean C. Bendall. Multiplexed single-cell metabolic profiles organize the spectrum of cytotoxic human t cells. bioRxiv, 2020. doi:10.1101/2020.01.17.909796.

[JFZ+20]

Hartland W Jackson, Jana R Fischer, Vito RT Zanotelli, H Raza Ali, Robert Mechera, Savas D Soysal, Holger Moch, Simone Muenst, Zsuzsanna Varga, Walter P Weber, and others. The single-cell pathology landscape of breast cancer. Nature, 578(7796):615–620, 2020.

[KHM20]

Kenji Kamimoto, Christy M. Hoffmann, and Samantha A. Morris. Celloracle: dissecting cell identity via network inference and in silico gene perturbation. bioRxiv, 2020. doi:10.1101/2020.02.17.947416.

[LGM+20]

Tim Lohoff, Shila Ghazanfar, Alsu Missarova, Noushin Koulena, Nico Pierson, Jonathan A Griffiths, Evan S Bardot, Chee-Huat Linus Eng, Richard CV Tyser, Ricard Argelaguet, and others. Highly multiplexed spatially resolved gene expression profiling of mouse organogenesis. bioRxiv, 2020.

[MBME+18]

Jeffrey R Moffitt, Dhananjay Bambah-Mukku, Stephen W Eichhorn, Eric Vaughn, Karthik Shekhar, Julio D Perez, Nimrod D Rubinstein, Junjie Hao, Aviv Regev, Catherine Dulac, and Xiaowei Zhuang. Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region. Science, 2018. doi:10.1126/science.aau5324.

[PSK+22]

Giovanni Palla, Hannah Spitzer, Michal Klein, David Fischer, Anna Christina Schaar, Louis Benedikt Kuemmerle, Sergei Rybakov, Ignacio L. Ibarra, Olle Holmberg, Isaac Virshup, Mohammad Lotfollahi, Sabrina Richter, and Fabian J. Theis. Squidpy: a scalable framework for spatial omics analysis. Nature Methods, 19(2):171–178, Feb 2022. doi:10.1038/s41592-021-01358-2.

[RA10]

Sergio J Rey and Luc Anselin. Pysal: a python library of spatial analytical methods. In Handbook of applied spatial analysis, pages 175–193. Springer, 2010. doi:10.1007/978-3-642-03647-7_11.

[SMK+20]

Robert R Stickels, Evan Murray, Pawan Kumar, Jilong Li, Jamie L Marshall, Daniela J Di Bella, Paola Arlotta, Evan Z Macosko, and Fei Chen. Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Nat. Biotechnol., 2020. doi:10.1038/s41587-020-0739-1.

[TureiKorcsmarosSR16]

Dénes Türei, Tamás Korcsmáros, and Julio Saez-Rodriguez. Omnipath: guidelines and gateway for literature-curated signaling pathway resources. Nature methods, 13(12):966–967, 2016. doi:10.1038/nmeth.4077.