Biophysical modeling with variational autoencoders for bimodal, single-cell RNA sequencing data

La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Melsted, P. et al. Modular, efficient and constant-memory single-cell RNA-seq preprocessing. Nat. Biotechnol. 39, 813–818 (2021).Article 
CAS 
PubMed 

Google Scholar 
Peterson, V. M. et al. Multiplexed quantification of proteins and transcripts in single cells. Nat. Biotechnol. 35, 936–939 (2017).Article 
CAS 
PubMed 

Google Scholar 
Mimitou, E. P. et al. Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells. Nat. Methods 16, 409–412 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chung, H. et al. Joint single-cell measurements of nuclear proteins and RNA in vivo. Nat. Methods 18, 1204–1212 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
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).Article 

Google Scholar 
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).Article 
PubMed 
PubMed Central 

Google Scholar 
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).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
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).Article 
CAS 
PubMed 

Google Scholar 
Gayoso, A. et al. Joint probabilistic modeling of single-cell multi-omic data with totalVI. Nat. Methods 18, 272–282 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Gayoso, A. et al. A Python library for probabilistic analysis of single-cell omics data. Nat. Biotechnol. 40, 163–166 (2022).Article 
CAS 
PubMed 

Google Scholar 
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).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
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).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
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).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y. & Tyagi, S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309 (2006).Article 
PubMed 
PubMed Central 

Google Scholar 
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).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sanchez, A. & Golding, I. Genetic determinants and cellular constraints in noisy gene expression. Science 342, 1188–1193 (2013).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Singh, A. & Bokes, P. Consequences of mRNA transport on stochastic variability in protein levels. Biophys. J. 103, 1087–1096 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
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).Article 
CAS 
PubMed 

Google Scholar 
Yao, Z. et al. A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex. Nature 598, 103–110 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
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).Article 
PubMed 
PubMed Central 

Google Scholar 
Ulland, T. K. & Colonna, M. Trem2 – a key player in microglial biology and alzheimer disease. Nat. Rev. Neurol. 14, 667–675 (2018).Article 
CAS 
PubMed 

Google Scholar 
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).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ham, L., Brackston, R. D. & Stumpf, M. P. H. Extrinsic noise and heavy-tailed laws in gene expression. Phys. Rev. Lett. 124, 108101 (2020).Article 
CAS 
PubMed 

Google Scholar 
Elowitz, M. B., Levine, A. J., Siggia, E. D. & Swain, P. S. Stochastic gene expression in a single cell. Science 297, 1183–1186 (2002).Article 
CAS 
PubMed 

Google Scholar 
Gorin, G. & Pachter, L. Length biases in single-cell RNA sequencing of pre-mRNA. Biophys. Rep. 3, 100097 (2023).CAS 

Google Scholar 
Svensson, V., Gayoso, A., Yosef, N. & Pachter, L. Interpretable factor models of single-cell RNA-seq via variational autoencoders. Bioinformatics 36, 3418–3421 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wang, J. et al. Gene expression distribution deconvolution in single-cell RNA sequencing. Proc. Natl Acad. Sci. USA 115, E6437–E6446 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
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).Article 
PubMed 
PubMed Central 

Google Scholar 
Desai, R. V. et al. A DNA repair pathway can regulate transcriptional noise to promote cell fate transitions. Science 373, eabc6506 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
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).

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