La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Melsted, P. et al. Modular, efficient and constant-memory single-cell RNA-seq preprocessing. Nat. Biotechnol. 39, 813–818 (2021).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Peterson, V. M. et al. Multiplexed quantification of proteins and transcripts in single cells. Nat. Biotechnol. 35, 936–939 (2017).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Mimitou, E. P. et al. Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells. Nat. Methods 16, 409–412 (2019).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Chung, H. et al. Joint single-cell measurements of nuclear proteins and RNA in vivo. Nat. Methods 18, 1204–1212 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Reyes, M., Billman, K., Hacohen, N. & Blainey, P. C. Simultaneous profiling of gene expression and chromatin accessibility in single cells. Adv. Biosyst. 3, 11 (2019).ArticleÂ
Google ScholarÂ
De Rop, F. et al. HyDrop enables droplet based single-cell ATAC-seq and single-cell RNA-seq using dissolvable hydrogel beads. eLife 11, e73971 (2022).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Gorin, G., Vastola, J. J., Fang, M. & Pachter, L. Interpretable and tractable models of transcriptional noise for the rational design of single-molecule quantification experiments. Nat. Commun. 13, 7620 (2022).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Svensson, V., Vento-Tormo, R. & Teichmann, S. A. Exponential scaling of single-cell RNA-seq in the past decade. Nat. Protoc. 13, 599–604 (2018).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Gayoso, A. et al. Joint probabilistic modeling of single-cell multi-omic data with totalVI. Nat. Methods 18, 272–282 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Gayoso, A. et al. A Python library for probabilistic analysis of single-cell omics data. Nat. Biotechnol. 40, 163–166 (2022).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Lin, X., Tian, T., Wei, Z. & Hakonarson, H. Clustering of single-cell multi-omics data with a multimodal deep learning method. Nat. Commun. 13, 7705 (2022).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Lopez, R., Regier, J., Cole, M. B., Jordan, M. I. & Yosef, N. Deep generative modeling for single-cell transcriptomics. Nat. Methods 15, 1053–1058 (2018).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Ashuach, T., Reidenbach, D. A., Gayoso, A. & Yosef, N. PeakVI: a deep generative model for single-cell chromatin accessibility analysis. Cell Rep. Methods 2, 100182 (2022).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y. & Tyagi, S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309 (2006).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Dar, R. D. et al. Transcriptional burst frequency and burst size are equally modulated across the human genome. Proc. Natl Acad. Sci. USA 109, 17454–17459 (2012).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Sanchez, A. & Golding, I. Genetic determinants and cellular constraints in noisy gene expression. Science 342, 1188–1193 (2013).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Singh, A. & Bokes, P. Consequences of mRNA transport on stochastic variability in protein levels. Biophys. J. 103, 1087–1096 (2012).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Gorin, G., Carilli, M., Chari, T. & Pachter, L. Spectral neural approximations for models of transcriptional dynamics. Biophys. J. https://doi.org/10.1016/j.bpj.2024.04.034 (2024).Pearl, J. Causal inference in statistics: an overview. Stat. Surveys 3, 96–146 (2009).Takei, Y. et al. High-resolution spatial multi-omics reveals cell-type specific nuclear compartments. Preprint at bioRxiv https://doi.org/10.1101/2023.05.07.539762 (2023).Battich, N. et al. Sequencing metabolically labeled transcripts in single cells reveals mRNA turnover strategies. Science 367, 1151–1156 (2020).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Yao, Z. et al. A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex. Nature 598, 103–110 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Kuang, X. L. et al. Spatio-temporal expression of a novel neuron-derived neurotrophic factor (NDNF) in mouse brains during development. BMC Neurosci. 11, 137 (2010).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Ulland, T. K. & Colonna, M. Trem2 – a key player in microglial biology and alzheimer disease. Nat. Rev. Neurol. 14, 667–675 (2018).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Munsky, B., Li, G., Fox, Z. R., Shepherd, D. P. & Neuert, G. Distribution shapes govern the discovery of predictive models for gene regulation. Proc. Natl Acad. Sci. USA 115, 7533–7538 (2018).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Ham, L., Brackston, R. D. & Stumpf, M. P. H. Extrinsic noise and heavy-tailed laws in gene expression. Phys. Rev. Lett. 124, 108101 (2020).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Elowitz, M. B., Levine, A. J., Siggia, E. D. & Swain, P. S. Stochastic gene expression in a single cell. Science 297, 1183–1186 (2002).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Gorin, G. & Pachter, L. Length biases in single-cell RNA sequencing of pre-mRNA. Biophys. Rep. 3, 100097 (2023).CASÂ
Google ScholarÂ
Svensson, V., Gayoso, A., Yosef, N. & Pachter, L. Interpretable factor models of single-cell RNA-seq via variational autoencoders. Bioinformatics 36, 3418–3421 (2020).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Wang, J. et al. Gene expression distribution deconvolution in single-cell RNA sequencing. Proc. Natl Acad. Sci. USA 115, E6437–E6446 (2018).CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Paszke, A. et al. PyTorch: an imperative style, high-performance deep learning library. In Advances in Neural Information Processing Systems 32 (eds Wallach, H. et al.) 8024–8035 (Curran Associates, 2019).Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 15 (2018).ArticleÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Desai, R. V. et al. A DNA repair pathway can regulate transcriptional noise to promote cell fate transitions. Science 373, eabc6506 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Takei, Y., Yang, Y. & Cai, L. High-resolution spatial multi-omics datasets. Zenodo https://doi.org/10.5281/zenodo.7693825 (2023).Carilli, M., Gorin, G., Choi, Y., Chari, T. & Pachter, L. biVI supporting data. Zenodo https://doi.org/10.5281/zenodo.10530877 (2024).