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Representation learning of RNA velocity reveals robust cell transitions [article]

Chen Qiao, Yuanhua Huang
2021 bioRxiv   pre-print
Here, we present VeloAE, a tailored representation learning method to learn a low-dimensional representation of RNA velocity on which cell transitions can be robustly estimated.  ...  RNA velocity is a promising technique to reveal transient cellular dynamics among a heterogeneous cell population and quantify their transitions from single-cell transcriptome experiments.  ...  The compact form of projecting velocities of all cells using matrix algebra is: V z = encode(S + V) − encode(S) ∈ R N ×dz (6) Cell transitions from low-dimensional representations 225 With low-dimensional  ... 
doi:10.1101/2021.03.19.436127 fatcat:jg6ibnbg7ffnvffn2ziuwo5e5y

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

F. Alexander Wolf, Fiona K. Hamey, Mireya Plass, Jordi Solana, Joakim S. Dahlin, Berthold Göttgens, Nikolaus Rajewsky, Lukas Simon, Fabian J. Theis
2019 Genome Biology  
Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions.  ...  Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions (  ...  Finally, we show how PAGA abstracts transition graphs, for instance, from RNA velocity and compare to previous trajectory-inference algorithms.  ... 
doi:10.1186/s13059-019-1663-x pmid:30890159 pmcid:PMC6425583 fatcat:vn5exscyl5bhxevezn2kvsymiu

Mapping Vector Field of Single Cells [article]

Xiaojie Qiu, Yan Zhang, Dian Yang, Shayan Hosseinzadeh, Li Wang, Ruoshi Yuan, Song Xu, Yian Ma, Joseph Replogle, Spyros Darmanis, Jianhua Xing, Jonathan Weissman
2019 bioRxiv   pre-print
Understanding how gene expression in single cells progress over time is vital for revealing the mechanisms governing cell fate transitions.  ...  This work thus foreshadows the possibility of predicting long-term trajectories of cells during a dynamic process instead of short time velocity estimates.  ...  One additional benefit of studying protein velocity is that, compared to RNA expression, proteins are often a better representation of cell states because they are the direct executors of biological processes  ... 
doi:10.1101/696724 fatcat:xoqks7ostnan3hiucv6q4yio6i

scDVF: Data-driven Single-cell Transcriptomic Deep Velocity Field Learning with Neural Ordinary Differential Equations [article]

Zhanlin Chen, William Casey King, Mark Gerstein, Jing Zhang
2022 bioRxiv   pre-print
Recent advances in single-cell RNA sequencing technology provided unprecedented opportunities to simultaneously measure the gene expression profile and the transcriptional velocity of individual cells,  ...  Benchmarking with state-of-the-art vector-field learning methods shows that scDVF can improve representation accuracy by at least 50%.  ...  Acknowledgments Funding: Research reported in this publication was supported by the National Institutes of Health under award numbers [insert here].  ... 
doi:10.1101/2022.02.15.480564 fatcat:ky7fssxkyzeqncatyeavfphdwq

Revealing routes of cellular differentiation by single-cell RNA-seq

Dominic Grün
2018 Current Opinion in Systems Biology  
It remains one of the major challenges to understand how nature has designed such robust and reproducible regulatory mechanisms.  ...  The recent availability of large-scale sensitive single-cell RNAseq protocols has enabled the generation of snapshot data covering the entire spectrum of cell states in a system of interest.  ...  Acknowledgements I thank Nina Cabezas-Wallscheid, Roman Sankowski, and Josip Herman for critical reading of the manuscript. The work was financially supported by the Max Planck Society.  ... 
doi:10.1016/j.coisb.2018.07.006 fatcat:t44u27lsarei7n2osuwvqlubay

Protein velocity and acceleration from single-cell multiomics experiments

Gennady Gorin, Valentine Svensson, Lior Pachter
2020 Genome Biology  
To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages estimates of unprocessed transcript and protein abundances  ...  The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots.  ...  Peer review information Barbara Cheifet was the primary editor of this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.  ... 
doi:10.1186/s13059-020-1945-3 pmid:32070398 fatcat:zgprgoev4bb2fgllowr7y4pfeu

Integrating temporal single-cell gene expression modalities for trajectory inference and disease prediction [article]

Jolene S. Ranek, Natalie Stanley, Jeremy E. Purvis
2022 bioRxiv   pre-print
RNA velocity infers the direction and speed of transcriptional changes in individual cells, yet it is unclear how these temporal gene expression modalities may be leveraged for predictive modeling of cellular  ...  Current methods for analyzing single-cell datasets have relied primarily on static gene expression measurements to characterize the molecular state of individual cells.  ...  This poses two fundamental challenges for robust prediction of the dynamic progression of cell state.  ... 
doi:10.1101/2022.03.01.482381 fatcat:zvs6pljzqrbplmur4vj6bpecza

CellRank for directed single-cell fate mapping [article]

Marius Lange, Volker Bergen, Michal Klein, Manu Setty, Bernhard Reuter, Mostafa Bakhti, Heiko Lickert, Meshal Ansari, Janine Schniering, Herbert B. Schiller, Dana Pe'er, Fabian J Theis
2020 bioRxiv   pre-print
Our approach combines the robustness of trajectory inference with directional information from RNA velocity, derived from ratios of spliced to unspliced reads.  ...  Computational trajectory inference enables the reconstruction of cell-state dynamics from single-cell RNA sequencing experiments.  ...  Tritschler for helping us with the biological interpretation of results, F. Paul for guidance regarding PCCA and GPCCA, G.  ... 
doi:10.1101/2020.10.19.345983 fatcat:zqtjfglgvjgddahsulxgvgxyfi

Concepts and limitations for learning developmental trajectories from single cell genomics

Sophie Tritschler, Maren Büttner, David S. Fischer, Marius Lange, Volker Bergen, Heiko Lickert, Fabian J. Theis
2019 Development  
Nowadays, tens of thousands of cells are routinely sequenced in single cell-based methods and even more are expected to be analysed in the future.  ...  Single cell genomics has become a popular approach to uncover the cellular heterogeneity of progenitor and terminally differentiated cell types with great precision.  ...  We would like to thank Anika Böttcher for helping with conceptualisation of this Review. Competing interests The authors declare no competing or financial interests.  ... 
doi:10.1242/dev.170506 pmid:31249007 fatcat:fhvgg6uezndonefqb3cdt4gkvy

Generalizing RNA velocity to transient cell states through dynamical modeling [article]

Volker Bergen, Marius Lange, Stefan Peidli, F. Alexander Wolf, Fabian J Theis
2019 bioRxiv   pre-print
The introduction of RNA velocity in single cells has opened up new ways of studying cellular differentiation.  ...  This generalizes RNA velocity to a wide variety of systems comprising transient cell states, which are common in development and in response to perturbations.  ...  As such, PAGA 7 has made a first suggestion for inferring directed abstracted representations of trajectories through RNA velocity.  ... 
doi:10.1101/820936 fatcat:irokqdgucjgjxnrur2lshnrmde

Cytopath: Simulation based inference of differentiation trajectories from RNA velocity fields [article]

Revant Gupta, Dario Cerletti, Gilles Gut, Annette Oxenius, Manfred Claassen
2020 bioRxiv   pre-print
We report Cytopath, a method for trajectory inference that takes advantage of transcriptional activity information from RNA velocity of single cells to perform trajectory inference.  ...  Trajectory inference constitutes a frequent step in interpreting single-cell RNA sequencing studies.  ...  For Cytopath, in addition to the projection the original RNA velocity field was used to infer cell to cell transitions. Pancreatic endocrinogenesis.  ... 
doi:10.1101/2020.12.21.423801 fatcat:6tdjyccjrfcplm53zcpctfriuq

Deciphering Cell Fate Decision by Integrated Single-Cell Sequencing Analysis

Sagar, Dominic Grün
2020 Annual Review of Biomedical Data Science  
Here, we review single-cell RNA sequencing and sequencing of other modalities as methods to elucidate the molecular underpinnings of lineage specification.  ...  mechanistic insights into the process of cell fate decision.  ...  RNA velocity is a notable exception, as the ratio of spliced and unspliced mRNA is used to predict the future state of the cell.  ... 
doi:10.1146/annurev-biodatasci-111419-091750 pmid:32780577 pmcid:PMC7115822 fatcat:ecayod5czbaapoazv7mbbpaxf4

Modeling Global Dynamics from Local Snapshots with Deep Generative Neural Networks [article]

Scott Gigante, David van Dijk, Kevin Moon, Alexander Strzalkowski, Guy Wolf, Smita Krishnaswamy
2019 arXiv   pre-print
We perform three case studies in which we apply DyMoN to different types of biological systems and extract features of the dynamics in each case by examining the learned model.  ...  In order to model the dynamics of such systems given snapshot data, or local transitions, we present a deep neural network framework we call Dynamics Modeling Network or DyMoN.  ...  the transition velocity vector ∆ θ (x).  ... 
arXiv:1802.03497v5 fatcat:vmweffqakbexreof6hyeigoio4

Defining Epidermal Basal Cell States during Skin Homeostasis and Wound Healing Using Single-Cell Transcriptomics

Daniel Haensel, Suoqin Jin, Peng Sun, Rachel Cinco, Morgan Dragan, Quy Nguyen, Zixuan Cang, Yanwen Gong, Remy Vu, Adam L. MacLean, Kai Kessenbrock, Enrico Gratton (+2 others)
2020 Cell Reports  
Pseudotemporal trajectory and RNA velocity analyses predict a quasi-linear differentiation hierarchy where basal cells progress from Col17a1Hi/Trp63Hi state to early-response state, proliferate at the  ...  Using single-cell RNA sequencing coupled with RNAScope and fluorescence lifetime imaging, we identify three non-proliferative and one proliferative basal cell state in homeostatic skin that differ in metabolic  ...  ACKNOWLEDGMENTS We thank the Genomics High Throughput Facility and the Institute for Immunology FACS Core Facility at University of California, Irvine (UCI) for expert service.  ... 
doi:10.1016/j.celrep.2020.02.091 pmid:32187560 pmcid:PMC7218802 fatcat:ug7tadqpmvco3f3ixv2xhdyf7a

1458 EMT-inhibiting transcription factor Ovol2 regulates directional cell migration and proliferation in adult skin epithelia

D. Haensel, P. Sun, A. MacLean, S. Jin, X. Ma, Q. Nie, X. Dai
2018 Journal of Investigative Dermatology  
Graphical Abstract Highlights d scRNA-seq identifies four epidermal basal cell states in homeostatic adult skin d Computational analysis supports a "hierarchical" model of epidermal homeostasis d Basal  ...  cell states are metabolically distinct and spatially partitioned in wounded skin d Epidermal basal cells show enhanced cell fate and state plasticity during wound healing  ...  Inclusion of these two HFSC clusters in RNA velocity analysis of WO epidermal basal cells revealed velocity arrows pointing from Cd34 Low HFSCs to ER/GA epidermal basal cells ( Figure S7G ), raising the  ... 
doi:10.1016/j.jid.2018.03.1476 fatcat:2m5yr37qmree7kgsbzvyvx42ai
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