References

References#

[DDHZM+23]

Carlo De Donno, Soroor Hediyeh-Zadeh, Amir Ali Moinfar, Marco Wagenstetter, Luke Zappia, Mohammad Lotfollahi, and Fabian J Theis. Population-level integration of single-cell datasets enables multi-scale analysis across samples. Nature Methods, 20(11):1683–1692, 2023.

[EY25]

Can Ergen and Nir Yosef. Resolvi-addressing noise and bias in spatial transcriptomics. bioRxiv, pages 2025–01, 2025.

[GLX+22]

Adam Gayoso, Romain Lopez, Galen Xing, Pierre Boyeau, Valeh Valiollah Pour Amiri, Justin Hong, Katherine Wu, Michael Jayasuriya, Edouard Mehlman, Maxime Langevin, and others. A python library for probabilistic analysis of single-cell omics data. Nature biotechnology, 40(2):163–166, 2022.

[HBB19]

Brian Hie, Bryan Bryson, and Bonnie Berger. Efficient integration of heterogeneous single-cell transcriptomes using scanorama. Nature biotechnology, 37(6):685–691, 2019.

[KMF+19]

Ilya Korsunsky, Nghia Millard, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, Michael Brenner, Po-ru Loh, and Soumya Raychaudhuri. Fast, sensitive and accurate integration of single-cell data with harmony. Nature methods, 16(12):1289–1296, 2019.

[LIB+25]

Nathan Levy, Florian Ingelfinger, Artemii Bakulin, Giacomo Cinnirella, Pierre Boyeau, Boaz Nadler, Can Ergen, and Nir Yosef. Scviva: a probabilistic framework for representation of cells and their environments in spatial transcriptomics. bioRxiv, pages 2025–06, 2025.

[LRC+18]

Romain Lopez, Jeffrey Regier, Michael B Cole, Michael I Jordan, and Nir Yosef. Deep generative modeling for single-cell transcriptomics. Nature methods, 15(12):1053–1058, 2018.

[LButtnerC+22]

Malte D Luecken, Maren Büttner, Kridsadakorn Chaichoompu, Anna Danese, Marta Interlandi, Michaela F Müller, Daniel C Strobl, Luke Zappia, Martin Dugas, Maria Colomé-Tatché, and others. Benchmarking atlas-level data integration in single-cell genomics. Nature methods, 19(1):41–50, 2022.

[VBH+23]

Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Philipp Angerer, Volker Bergen, Pierre Boyeau, Maren Büttner, Gokcen Eraslan, David Fischer, Max Frank, Justin Hong, Michal Klein, Marius Lange, Romain Lopez, Mohammad Lotfollahi, Malte D. Luecken, Fidel Ramirez, Jeffrey Regier, Sergei Rybakov, Anna C. Schaar, Valeh Valiollah Pour Amiri, Philipp Weiler, Galen Xing, Bonnie Berger, Dana Pe'er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle, and Fabian J. Theis and. The scverse project provides a computational ecosystem for single-cell omics data analysis. Nature Biotechnology, apr 2023. URL: https://doi.org/10.1038%2Fs41587-023-01733-8, doi:10.1038/s41587-023-01733-8.

[WKF+19]

Joshua D Welch, Velina Kozareva, Ashley Ferreira, Charles Vanderburg, Carly Martin, and Evan Z Macosko. Single-cell multi-omic integration compares and contrasts features of brain cell identity. Cell, 177(7):1873–1887, 2019.

[WAT18]

F Alexander Wolf, Philipp Angerer, and Fabian J Theis. Scanpy: large-scale single-cell gene expression data analysis. Genome biology, 19(1):15, 2018.

[XLM+21]

Chenling Xu, Romain Lopez, Edouard Mehlman, Jeffrey Regier, Michael I Jordan, and Nir Yosef. Probabilistic harmonization and annotation of single-cell transcriptomics data with deep generative models. Molecular systems biology, 17(1):e9620, 2021.