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An automated workflow for parallel processing of large multiview SPIM recordings

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Item Type:Article
Title:An automated workflow for parallel processing of large multiview SPIM recordings
Creators Name:Schmied, C. and Steinbach, P. and Pietzsch, T. and Preibisch, S. and Tomancak, P.
Abstract:Selective Plane Illumination Microscopy (SPIM) allows to image developing organisms in 3D at unprecedented temporal resolution over long periods of time. The resulting massive amounts of raw image data requires extensive processing interactively via dedicated graphical user interface (GUI) applications. The consecutive processing steps can be easily automated and the individual time points can be processed independently, which lends itself to trivial parallelization on a high performance computing (HPC) cluster. Here we introduce an automated workflow for processing large multiview, multi-channel, multi-illumination time-lapse SPIM data on a single workstation or in parallel on a HPC cluster. The pipeline relies on snakemake to resolve dependencies among consecutive processing steps and can be easily adapted to any cluster environment for processing SPIM data in a fraction of the time required to collect it.
Keywords:Computing Methodologies, Microscopy, Programming Languages, Software, Workflow
Source:Bioinformatics
ISSN:1367-4803
Publisher:Oxford University Press (U.K.)
Volume:32
Number:7
Page Range:1112-1114
Date:1 April 2016
Additional Information:Availability: The code is distributed free and open source under the MIT license http://opensource.org/licenses/MIT. The source code can be downloaded from github: https://github.com/mpicbgscicomp/snakemake-work-flows. Documentation can be found here: http://fiji.sc/Automated_workflow_for_parallel_Multi-view_Reconstruction. Contact: schmied@mpi-cbg.de
Official Publication:https://doi.org/10.1093/bioinformatics/btv706
PubMed:View item in PubMed
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https://edoc.mdc-berlin.de/17578/Preprint version

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