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Accurate Reconstruction of Cell and Particle Tracks from 3D Live Imaging Data.

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Title: Accurate Reconstruction of Cell and Particle Tracks from 3D Live Imaging Data.
Authors: Liepe, J
Sim, A
Weavers, H
Ward, L
Martin, P
Stumpf, MP
Item Type: Journal Article
Abstract: Spatial structures often constrain the 3D movement of cells or particles in vivo, yet this information is obscured when microscopy data are analyzed using standard approaches. Here, we present methods, called unwrapping and Riemannian manifold learning, for mapping particle-tracking data along unseen and irregularly curved surfaces onto appropriate 2D representations. This is conceptually similar to the problem of reconstructing accurate geography from conventional Mercator maps, but our methods do not require prior knowledge of the environments' physical structure. Unwrapping and Riemannian manifold learning accurately recover the underlying 2D geometry from 3D imaging data without the need for fiducial marks. They outperform standard x-y projections, and unlike standard dimensionality reduction techniques, they also successfully detect both bias and persistence in cell migration modes. We demonstrate these features on simulated data and zebrafish and Drosophila in vivo immune cell trajectory datasets. Software packages that implement unwrapping and Riemannian manifold learning are provided.
Issue Date: 21-Jul-2016
Date of Acceptance: 3-Jun-2016
URI: http://hdl.handle.net/10044/1/39567
DOI: https://dx.doi.org/10.1016/j.cels.2016.06.002
ISSN: 2405-4720
Publisher: Elsevier (Cell Press)
Start Page: 102
End Page: 107
Journal / Book Title: Cell Systems
Volume: 3
Issue: 1
Copyright Statement: © 2016 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Human Frontier Science Program
Biotechnology and Biological Sciences Research Council (BBSRC)
Funder's Grant Number: EP/I017267/1
RGP0061/2011
BB/K017284/1
Publication Status: Published
Appears in Collections:Faculty of Natural Sciences