References

GayosoSteier21

Adam Gayoso*, Zoë Steier*, Romain Lopez, Jeffrey Regier, Kristopher L Nazor, Aaron Streets, Nir Yosef (2021), Joint probabilistic modeling of single-cell multi-omic data with totalVI, Nature Methods.

Xu21

Chenling Xu*, Romain Lopez*, Edouard Mehlman*, Jeffrey Regier, Michael I. Jordan, Nir Yosef (2021), Probabilistic harmonization and annotation of single-cell transcriptomics data with deep generative models, Molecular Systems Biology.

Andersson20

Alma Andersson, Joseph Bergenstråhle, Michaela Asp, Ludvig Bergenstråhle, Aleksandra Jurek, José Fernández Navarro & Joakim Lundeberg (2020), Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography, Communications Biology.

Lotfollahi20

Mohammad Lotfollahi*, Mohsen Naghipourfar*, Malte D. Luecken, Matin Khajavi, Maren Büttner, Ziga Avsec, Alexander V. Misharin, Fabian J. Theis (2020), Query to reference single-cell integration with transfer learning, bioRxiv.

Svensson20

Valentine Svensson, Adam Gayoso, Nir Yosef, Lior Pachter (2020), Interpretable factor models of single-cell RNA-seq via variational autoencoders, Bioinformatics.

Boyeau19

Pierre Boyeau, Romain Lopez, Jeffrey Regier, Adam Gayoso, Michael I. Jordan, Nir Yosef (2019), Deep generative models for detecting differential expression in single cells, Machine Learning in Computational Biology (MLCB).

Clivio19

Oscar Clivio, Romain Lopez, Jeffrey Regier, Adam Gayoso, Michael I. Jordan, Nir Yosef (2019), Detecting zero-inflated genes in single-cell transcriptomics data, Machine Learning in Computational Biology (MLCB).

Lopez19

Romain Lopez*, Achille Nazaret*, Maxime Langevin*, Jules Samaran*, Jeffrey Regier*, Michael I. Jordan, Nir Yosef (2019), A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements, ICML Workshop on Computational Biology.

Bernstein19

Nicholas J. Bernstein, , Nicole L. Fong, Irene Lam, Margaret A. Roy, David G. Hendrickson, and David R. Kelley (2020), Solo: doublet identification in single-cell RNA-Seq via semi-supervised deep learning, Cell Systems.

Zhang19

Allen W. Zhang, Ciara O’Flanagan, Elizabeth A. Chavez, Jamie LP Lim, Nicholas Ceglia, Andrew McPherson, Matt Wiens et al. (2019), Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling, Nature Methods.

Lopez18

Romain Lopez, Jeffrey Regier, Michael Cole, Michael I. Jordan, Nir Yosef (2018), Deep generative modeling for single-cell transcriptomics, Nature Methods.