An automated workflow for parallel processing of large multiview SPIM recordings

Bioinformatics. 2016 Apr 1;32(7):1112-4. doi: 10.1093/bioinformatics/btv706. Epub 2015 Dec 1.

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, multichannel, multiillumination 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.

Availability and implementation: 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/mpicbg-scicomp/snakemake-workflows Documentation can be found here: http://fiji.sc/Automated_workflow_for_parallel_Multiview_Reconstruction

Contact: : schmied@mpi-cbg.de

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

  • Computing Methodologies
  • Microscopy*
  • Programming Languages
  • Software*
  • Workflow*