  Volume electron microscopy is the method of choice for the in-situ
interrogation of cellular ultrastructure at the nanometer scale. Recent
technical advances have led to a rapid increase in large raw image datasets
that require computational strategies for segmentation and spatial analysis. In
this protocol, we describe a practical and annotation-efficient pipeline for
organelle-specific segmentation, spatial analysis, and visualization of large
volume electron microscopy datasets using freely available, user-friendly
software tools that can be run on a single standard workstation. We
specifically target researchers in the life sciences with limited computational
expertise, who face the following tasks within their volume electron microscopy
projects: i) How to generate 3D segmentation labels for different types of cell
organelles while minimizing manual annotation efforts, ii) how to analyze the
spatial interactions between organelle instances, and iii) how to best
visualize the 3D segmentation results. To meet these demands we give detailed
guidelines for choosing the most efficient segmentation tools for the specific
cell organelle. We furthermore provide easily executable components for spatial
analysis and 3D rendering and bridge compatibility issues between freely
available open-source tools, such that others can replicate our full pipeline
starting from a raw dataset up to the final plots and rendered images. We
believe that our detailed description can serve as a valuable reference for
similar projects requiring special strategies for single- or multiple organelle
analysis which can be achieved with computational resources commonly available
to single-user setups.
