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Dynamic pseudo-time warping of complex single-cell trajectories

Van Hoan Do, Mislav Blažević, Pablo Monteagudo, Luka Borozan, Khaled Elbassioni, Sören Laue, Francisca Rojas Ringeling, Domagoj Matijević, View ORCID ProfileStefan Canzar
doi: https://doi.org/10.1101/522672
Van Hoan Do
4Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany
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Mislav Blažević
1Department of Mathematics, University of Osijek, Croatia
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Pablo Monteagudo
4Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany
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Luka Borozan
1Department of Mathematics, University of Osijek, Croatia
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Khaled Elbassioni
2Khalifa University of Science and Technology, Abu Dhabi, UAE
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Sören Laue
3Friedrich-Schiller-Universität Jena, Germany
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Francisca Rojas Ringeling
4Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany
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Domagoj Matijević
1Department of Mathematics, University of Osijek, Croatia
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Stefan Canzar
4Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany
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  • ORCID record for Stefan Canzar
  • For correspondence: canzar@genzentrum.lmu.de
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Abstract

Single-cell RNA sequencing enables the construction of trajectories describing the dynamic changes in gene expression underlying biological processes such as cell differentiation and development. The comparison of single-cell trajectories under two distinct conditions can illuminate the differences and similarities between the two and can thus be a powerful tool. Recently developed methods for the comparison of trajectories rely on the concept of dynamic time warping (dtw), which was originally proposed for the comparison of two time series. Consequently, these methods are restricted to simple, linear trajectories. Here, we adopt and theoretically link arboreal matchings to dtw and propose an algorithm to compare complex trajectories that more realistically contain branching points that divert cells into different fates. We implement a suite of exact and heuristic algorithms suitable for the comparison of trajectories of different characteristics in our tool Trajan. Trajan automatically pairs similar biological processes between conditions and aligns them in a globally consistent manner. In an alignment of singlecell trajectories describing human muscle differentiation and myogenic reprogramming, Trajan identifies and aligns the core paths without prior information. From Trajan’s alignment, we are able to reproduce recently reported barriers to reprogramming. In a perturbation experiment, we demonstrate the benefits in terms of robustness and accuracy of our model which compares entire trajectories at once, as opposed to a pairwise application of dtw. Trajan is available at https://github.com/canzarlab/Trajan.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 17, 2019.
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Dynamic pseudo-time warping of complex single-cell trajectories
Van Hoan Do, Mislav Blažević, Pablo Monteagudo, Luka Borozan, Khaled Elbassioni, Sören Laue, Francisca Rojas Ringeling, Domagoj Matijević, Stefan Canzar
bioRxiv 522672; doi: https://doi.org/10.1101/522672
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Dynamic pseudo-time warping of complex single-cell trajectories
Van Hoan Do, Mislav Blažević, Pablo Monteagudo, Luka Borozan, Khaled Elbassioni, Sören Laue, Francisca Rojas Ringeling, Domagoj Matijević, Stefan Canzar
bioRxiv 522672; doi: https://doi.org/10.1101/522672

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