Publications#
Journal Articles#
Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells. Adam Gayoso*, Philipp Weiler*, Mohammad Lotfollahi, Dominik Klein, Justin Hong, Aaron Streets, Fabian J. Theis, and Nir Yosef. Nature Methods (in press), 2023. [Paper]
The scverse project provides a computational ecosystem for single-cell omics data analysis
Isaac Virshup*, Danila Bredikhin*, Lukas Heumos*, Giovanni Palla*, Gregor Sturm*, Adam Gayoso*, Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J. Theis
Nature Biotechnology, 2023. [Paper]
An Empirical Bayes Method for Differential Expression Analysis of Single Cells with Deep Generative Models.
Pierre Boyeau, Jeffrey Regier, Adam Gayoso, Michael I. Jordan, Romain Lopez, Nir Yosef.
Proceedings of the National Academy of Sciences (in press), 2023. [Paper]
The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans.
The Tabula Sapiens Consortium*
Science, 2022. [Paper]
PeakVI: A deep generative model for single-cell chromatin accessibility analysis
Tal Ashuach, Daniel A. Reidenbach, Adam Gayoso, Nir Yosef.
Cell Reports Methods, 2022. [Paper]
A Python library for probabilistic analysis of single-cell omics data.
Adam Gayoso*, Romain Lopez*, Galen Xing*, Pierre Boyeau, Valeh Valiollah Pour Amiri, Justin Hong, Katherine Wu, Michael Jayasuriya, Edouard Mehlman, Maxime Langevin, Yining Liu, Jules Samaran, Gabriel Misrachi, Achille Nazaret, Oscar Clivio, Chenling Xu, Tal Ashuach, Mohammad Lotfollahi, Valentine Svensson, Eduardo da Veiga Beltrame, Vitalii Kleshchevnikov, Carlos Talavera-Lopez, Lior Pachter, Fabian J Theis, Aaron Streets, Michael I Jordan, Jeffrey Regier, and Nir Yosef.
Nature Biotechnology, 2022. [Paper][bioRxiv]
Cell2location maps fine-grained cell types in spatial transcriptomics.
Vitalii Kleshchevnikov, Artem Shmatko, Emma Dann, Alexander Aivazidis, Hamish W. King, Tong Li, Rasa Elmentaite, Artem Lomakin, Veronika Kedlian, Adam Gayoso, Mika Sarkin Jain, Jun Sung Park, Lauma Ramona, Elizabeth Tuck, Anna Arutyunyan, Roser Vento-Tormo, Moritz Gerstung, Louisa James, Oliver Stegle, Omer Ali Bayraktar.
Nature Biotechnology, 2022. [Paper]
Mapping single-cell data to reference atlases by transfer learning.
Mohammad Lotfollahi, Mohsen Naghipourfar, Malte D. Luecken, Matin Khajavi, Maren Büttner, Marco Wagenstetter, Ziga Avsec, Adam Gayoso, Nir Yosef, Marta Interlandi, Sergei Rybakov, Alexander V. Misharin, and Fabian J. Theis
Nature Biotechnology, 2021. [Paper]
Joint probabilistic modeling of single-cell multi-omic data with totalVI.
Adam Gayoso*, Zoë Steier*, Romain Lopez, Jeffrey Regier, Kristopher L Nazor, Aaron Streets, Nir Yosef.
Nature Methods, 2021. [Paper][bioRxiv]
Interpretable factor models of single-cell RNA-seq via variational autoencoders.
Valentine Svensson, Adam Gayoso, Nir Yosef, Lior Pachter.
Bioinformatics, 2020. [Paper]
Characterization of cell fate probabilities in single-cell data with Palantir.
Manu Setty, Vaidotas Kiseliovas, Jacob Levine, Adam Gayoso, Linas Mazutis, Dana Pe’er.
Nature Biotechnology, 2019. [Paper]
Stress-adaptive responses associated with high-level carbapenem resistance in kpc-producing klebsiella pneumoniae.
Sheila Adams-Sapper, Adam Gayoso, Lee. W. Riley.
Journal of Pathogens, 2018. [Paper]
Review Articles#
Enhancing scientific discoveries in molecular biology with deep generative models.
Romain Lopez, Adam Gayoso, Nir Yosef.
Molecular Systems Biology, 2020. [Paper]
Refereed Workshop Papers#
Deep generative modeling for quantifying sample-level heterogeneity in single-cell omics.
Pierre Boyeau*, Justin Hong*, Adam Gayoso, Michael I. Jordan, Elham Azizi, Nir Yosef.
Machine Learning in Computational Biology (MLCB), Oral presentation 2022. [Paper]
A joint model of RNA expression and surface protein abundance in single cells.
Adam Gayoso, Romain Lopez, Zoë Steier, Jeffrey Regier, Aaron Streets, Nir Yosef.
Machine Learning in Computational Biology (MLCB), 2020. [Paper]
Detecting zero-inflated genes in single-cell transcriptomics data.
Oscar Clivio, Romain Lopez, Jeffrey Regier, Adam Gayoso, Michael I. Jordan, Nir Yosef.
Machine Learning in Computational Biology (MLCB), Spotlight talk, 2020. [Paper]
Deep generative models for detecting differential expression in single cells.
Pierre Boyeau, Romain Lopez, Jeffrey Regier, Adam Gayoso, Michael I. Jordan, Nir Yosef.
Machine Learning in Computational Biology (MLCB), 2020. [Paper]