A Python library for probabilistic analysis of single-cell omics data

Probabilistic harmonization and annotation of single‐cell transcriptomics data with deep generative models

(2021) Chenling Xu et al.   Molecular Systems Biology

Joint probabilistic modeling of single-cell multi-omic data with totalVI

(2021) Adam Gayoso et al.   NATURE METHODS

Mapping single-cell data to reference atlases by transfer learning

(2021) Mohammad Lotfollahi et al.   NATURE BIOTECHNOLOGY

Solo: Doublet Identification in Single-Cell RNA-Seq via Semi-Supervised Deep Learning

(2020) Nicholas J. Bernstein et al.   Cell Systems

Single-cell multiomics: technologies and data analysis methods

(2020) Jeongwoo Lee et al.   EXPERIMENTAL AND MOLECULAR MEDICINE

Enhancing scientific discoveries in molecular biology with deep generative models

(2020) Romain Lopez et al.   Molecular Systems Biology

Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography

(2020) Alma Andersson et al.   Communications Biology

Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling

(2019) Allen W. Zhang et al.   NATURE METHODS

Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database

(2018) Luke Zappia et al.   PLoS Computational Biology

Deep generative modeling for single-cell transcriptomics

(2018) Romain Lopez et al.   NATURE METHODS

Revealing the vectors of cellular identity with single-cell genomics

(2016) Allon Wagner et al.   NATURE BIOTECHNOLOGY

Spatial reconstruction of single-cell gene expression data

(2015) Rahul Satija et al.   NATURE BIOTECHNOLOGY