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Reconstructing probabilistic trees of cellular differentiation from single-cell RNA-seq data [article]

Miriam Shiffman, William T. Stephenson, Geoffrey Schiebinger, Jonathan Huggins, Trevor Campbell, Aviv Regev, Tamara Broderick
2018 arXiv   pre-print
Here, we develop a full generative model for probabilistically reconstructing trees of cellular differentiation from single-cell RNA-seq data.  ...  While this work is motivated by cellular differentiation, we derive a tractable model that provides flexible densities for any data (coupled with an appropriate noise model) that arise from continuous  ...  Conclusions and future We take a Bayesian nonparametric approach to learning cell state from inherently noisy single-cell RNA-seq data of differentiating cells.  ... 
arXiv:1811.11790v1 fatcat:6ujpmcksofb2hlq7ewoprwngui

PROSSTT: probabilistic simulation of single-cell RNA-seq data for complex differentiation processes [article]

Nikolaos Papadopoulos, Rodrigo Gonzalo Parra, Johannes Soeding
2018 bioRxiv   pre-print
Single-cell RNA sequencing (scRNA-seq) is an enabling technology for the study of cellular differentiation and heterogeneity.  ...  From snapshots of the transcriptomic profiles of differentiating single cells, the cellular lineage tree that leads from a progenitor population to multiple types of differentiated cells can be derived  ...  To address these needs we developed PROSSTT (PRObabilistic Simulation of Single-cell RNA-seq Tree-like Topologies), a python package for simulating realistic scRNA-seq datasets of differentiating cells  ... 
doi:10.1101/256941 fatcat:5sixloidn5cp7gicbgddmva6qq

PROSSTT: probabilistic simulation of single-cell RNA-seq data for complex differentiation processes

Nikolaos Papadopoulos, R Gonzalo Parra, Johannes Söding, Jonathan Wren
2019 Bioinformatics  
Cellular lineage trees can be derived from single-cell RNA sequencing snapshots of differentiating cells. Currently, only datasets with simple topologies are available.  ...  PROSSTT can simulate scRNA-seq datasets for differentiation processes with lineage trees of any desired complexity, noise level, noise model and size.  ...  Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btz078 pmid:30715210 pmcid:PMC6748774 fatcat:nputsb6dbjhifceerxek6lasgu

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

Dominic Grün
2018 Current Opinion in Systems Biology  
Consequently, a large number of computational methods for the reconstruction of cellular differentiation trajectories have been developed.  ...  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

Deciphering Cell Fate Decision by Integrated Single-Cell Sequencing Analysis

Sagar, Dominic Grün
2020 Annual Review of Biomedical Data Science  
Studying cellular differentiation using single-cell genomic tools is paving the way for a detailed understanding of cellular behavior in health and disease.  ...  Here, we review single-cell RNA sequencing and sequencing of other modalities as methods to elucidate the molecular underpinnings of lineage specification.  ...  Reconstructing Differentiation Trajectories to Characterize Cell Fate Specification The reconstruction of differentiation trajectories from scRNA-seq data relies on the assumption that single-cell transcriptomes  ... 
doi:10.1146/annurev-biodatasci-111419-091750 pmid:32780577 pmcid:PMC7115822 fatcat:ecayod5czbaapoazv7mbbpaxf4

Breaking New Ground in the Landscape of Single-Cell Analysis

Kenji Kamimoto, Samantha A. Morris
2018 Cell Systems  
Application of this platform to diverse sources of single-cell data demonstrates its robustness and scalability, while the discovery of a new origin for rare gut tuft cells showcases the utility of p-Creode  ...  Here, we outline p-Creode, a new algorithm to construct multi-branching cell lineage trajectories from singlecell data.  ...  Using publicly available scRNA-seq data of alveolar epithelial cell differentiation obtained by the Fluidigm-C1 system and hematopoiesis data acquired by massively parallel single-cell RNA sequencing (  ... 
doi:10.1016/j.cels.2017.12.015 pmid:29401450 fatcat:ji6uyaa3k5bcriarqrbbp2ihqq

Single-cell RNA sequencing technologies and bioinformatics pipelines

Byungjin Hwang, Ji Hyun Lee, Duhee Bang
2018 Experimental and Molecular Medicine  
Single-cell RNA sequencing (scRNA-seq), for example, can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track the trajectories of distinct cell lineages in  ...  In this review, we will focus on technical challenges in single-cell isolation and library preparation and on computational analysis pipelines available for analyzing scRNA-seq data.  ...  Even though the primary focus of this article is RNA-seq-based methods, we also note that cellular hierarchy can also be reconstructed from proteomic 94, 95 or epigenomic measures 96 .  ... 
doi:10.1038/s12276-018-0071-8 pmid:30089861 pmcid:PMC6082860 fatcat:5hbi2tvtcrh4ble5ibj6eudjem

Computational modelling in single-cell cancer genomics: methods and future directions [article]

Allen W Zhang, Kieran R Campbell
2020 arXiv   pre-print
Single-cell technologies have revolutionized biomedical research by enabling scalable measurement of the genome, transcriptome, and proteome of multiple systems at single-cell resolution.  ...  However, the large quantities of high-dimensional, noisy data produced by single-cell assays can complicate data analysis, obscuring biological signals with technical artefacts.  ...  Acknowledgements We thank Sally Millett for the creation of the visualizations in Figure 1 . We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC).  ... 
arXiv:2005.01549v1 fatcat:6as2k6i5orfy7fby7xm7bz5way

Pinpointing Cell Identity in Time and Space

Anca F. Savulescu, Caron Jacobs, Yutaka Negishi, Laurianne Davignon, Musa M. Mhlanga
2020 Frontiers in Molecular Biosciences  
We refer to recent studies making use of single cell RNA-seq and/or image-based cell characterization, which highlight a need for such in-depth characterization of cell populations.  ...  Emerging data suggests that additional levels of information should be considered, including the subcellular spatial distribution of molecules such as RNA and protein, when classifying cells.  ...  For example, Monocle (Trapnell et al., 2014) , uses single-cell RNA-seq data collected at multiple time points to characterize the temporal aspect of gene expression.  ... 
doi:10.3389/fmolb.2020.00209 pmid:32923457 pmcid:PMC7456825 fatcat:uxuudvtgzfb3rer64tzriecsua

PhylEx: Accurate reconstruction of clonal structure via integrated analysis of bulk DNA-seq and single cell RNA-seq data [article]

Seong-Hwan Jun, Hosein Toosi, Jeff Mold, Camilla Engblom, Xinsong Chen, Ciara O'Flanagan, Michael Hagemann-Jensen, Rickard Sandberg, Samuel Aparicio, Johan Hartman, Andrew Roth, Jens Lagergren
2021 bioRxiv   pre-print
In the probabilistic model underlying PhylEx, the raw read counts from scRNA-seq follow a mixture of Beta-Binomial distributions, which accounts for the sparse nature of single-cell gene expression data  ...  AbstractWe propose PhylEx: a clonal-tree reconstruction method that integrates bulk genomics and single-cell transcriptomics data.  ...  A general and 425 flexible method for signal extraction from single-cell RNA-seq data. Nature communications, 9(1):1-17, 2018. 426 [22] Laurens van der Maaten and Geoffrey Hinton.  ... 
doi:10.1101/2021.02.16.431009 fatcat:nz3k4fxqbza5rcpiwza6ebwyja

Machine Intelligence in Single-Cell Data Analysis: Advances and New Challenges

Jiajia Liu, Zhiwei Fan, Weiling Zhao, Xiaobo Zhou
2021 Frontiers in Genetics  
We will start with the pre-processing of single-cell RNA sequencing (scRNA-seq) data, including data imputation, cross-platform batch effect removal, and cell cycle and cell-type identification.  ...  Next, we will introduce advanced data analysis tools and methods used for copy number variance estimate, single-cell pseudo-time trajectory analysis, phylogenetic tree inference, cellcell interaction,  ...  ACKNOWLEDGMENTS We thank the members of the Center for Computational Systems Medicine (CCSM) for valuable discussion.  ... 
doi:10.3389/fgene.2021.655536 pmid:34135939 pmcid:PMC8203333 fatcat:tp5v7gtdwnezjfrfef45ctidye

Single-Cell Transcriptomics Bioinformatics and Computational Challenges

Olivier B. Poirion, Xun Zhu, Travers Ching, Lana Garmire
2016 Frontiers in Genetics  
The emerging single-cell RNA-Seq (scRNA-Seq) technology holds the promise to revolutionize our understanding of diseases and associated biological processes at an unprecedented resolution.  ...  It opens the door to reveal intercellular heterogeneity and has been employed to a variety of applications, ranging from characterizing cancer cells subpopulations to elucidating tumor resistance mechanisms  ...  ACKNOWLEDGMENTS This research was supported by grants K01ES025434 awarded by NIEHS through funds provided by the trans-NIH Big Data to Knowledge (BD2K) initiative (, P20 COBRE GM103457  ... 
doi:10.3389/fgene.2016.00163 pmid:27708664 pmcid:PMC5030210 fatcat:d3ui6x46mrbxratberny4frysm

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  
Single cell genomics has become a popular approach to uncover the cellular heterogeneity of progenitor and terminally differentiated cell types with great precision.  ...  In contrast to other applications of single cell sequencing, where clustering approaches dominate, developmental systems are generally modelled using continuous structures, trajectories and trees.  ...  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

Lineage Tracing: Computational Reconstruction Goes Beyond the Limit of Imaging

Szu-Hsien Sam Wu, Ji-Hyun Lee, Bon-Kyoung Koo
2019 Molecules and Cells  
In this review, we will introduce such novel computational methods, starting from single-cell RNA sequencing-based lineage analysis to DNA barcoding or genetic scar analysis.  ...  Both are imaging-based approaches that have played a crucial role in the field of developmental biology as well as adult stem cell biology.  ...  Hindley for critical reading of the manuscript and to Sung-hwan Bae for graphic illustration. This work was supported by the ERC starting grant (Troy Stem Cells, 639050).  ... 
doi:10.14348/molcells.2019.0006 pmid:30764600 pmcid:PMC6399003 fatcat:x5wcwpbacnhw7bpvsp55xra6rq

Using single-cell multiple omics approaches to resolve tumor heterogeneity

Michael A. Ortega, Olivier Poirion, Xun Zhu, Sijia Huang, Thomas K. Wolfgruber, Robert Sebra, Lana X. Garmire
2017 Clinical and Translational Medicine  
Continuing advancements in single-cell technology and computational deconvolution of data will be critical for reconstructing patient specific intra-tumour features and developing more personalized cancer  ...  In addition, the development of new techniques for combining single-cell multi-omic strategies is providing a more precise understanding of factors contributing to cellular identity, function, and growth  ...  Acknowledgements We would like to thank all the members of the Garmire Lab for their helpful discussions and manuscript review.  ... 
doi:10.1186/s40169-017-0177-y pmid:29285690 pmcid:PMC5746494 fatcat:4o55gjckdfdurcrus4ftrldzbu
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