Equipment

1. Computational setup
   The computational work I describe can be done on any UNIX-based platform, such as Linux and MacOSX. All programs in the Bsoft package (Heymann, 2018a) can run on a single machine with multiple CPU cores. However, single particle analysis is computationally intensive and typically requires a cluster to run in a reasonable amount of time. The computational power needed scales with the number and size of particle images, as well as the choice of reference and processing parameters. In this particular case, I used approximately 900 CPU cores (Linux and MacOSX) in our cluster for the following tasks:
   
   1. Micrograph preprocessing: ~70 h for 1,354 micrographs, each with 50-54 frames.
   2. 2D alignment and classification of 39,536 particles of size 330 x 330: ~12 h over five iterations.
   3. 3D alignment of 26,702 particles of size 168 x 168: ~10 h over six iterations.
   4. 3D alignment of 26,702 particles of size 224 x 224: ~4 h over four iterations.
   Note: The times stated just provide a rough idea of how long it takes. The usage of a cluster is highly variable due to competition with multiple users and intermittent availability of nodes.
   

Software

1. Bsoft basics
   All of the processing I describe here can be done with the current version of Bsoft (version 2.0.6) (Heymann, 2018a).
   1. brun
      Bsoft contains a large number of command-line programs. The program brun can be used to launch these command line programs in a more interactive way. Typing any program name on the command line (without options) provides usage information, including all the options. The options for these programs can be abbreviated, as long as they are unique. All the programs have a “-verbose” option that sets the level of information generated. Without this option, no information will be generated. With quick tasks the verbosity level is typically set to 7, which will give image statistics and parameters for the operation being executed. With extensive tasks (such as aligning particle images or performing reconstructions), the verbosity is usually set to 1 to limit the information to the most important results.
   2. bshow
      The main program for interactive work is bshow. It presents the user with an image processing environment where many different operations can be performed. For some programs there are options to plot the output data in Postscript files. These are text files with the data encoded as tables that can be easily imported into other plotting programs for better visualization. The conventions in Bsoft adhere to those we specified in 2005 (Heymann et al., 2005). Because one can use operations other than Fourier transformation to calculate frequency terms, I use the term “frequency space” rather than “Fourier space”. Many of the programs in Bsoft have been parallelized using Grand Central Dispatch on Mac OSX and OpenMP on Linux and will automatically use as many cores as available. In some cases the user can specify the number of threads (i.e., cores) to use (e.g., breconstruct). The Bsoft package (Heymann, 2018a) is freely available at http://bsoft.ws.
2. Distributed processing
   The command line programs in Bsoft are executable in any Unix-like environment and from any commonly used script language (such as bash, perl and python). Because each particle is aligned on its own, the philosophy is to separate a set of particles into smaller subsets and run those on different machines. This means that one can use a heterogenous mixture of computers to distribute the tasks. We use the Peach distributed processing system (Leong et al., 2005), but the same can be done on any cluster with a proper queueing manager.
3. Validation as an integral part of the processing
   The success and validity of all micrograph processing depends on understanding the influence of noise and how to avoid bias imposed by user decisions. Most of the principles are laid out in Heymann (Heymann, 2018a). The best practices involve three recommendations:
   1. Process at least two independent sets of particle images–I typically split the set of micrographs into manageable subsets before processing.
   2. Use conservative resolution limits during particle alignment.
   3. Test the final reconstruction for coherency: i.e., whether the averages or reconstructions from particle images are better than from noise images.
   The assessments of the resolutions of reconstructions (i.e., detail in the maps) are performed by comparing maps from independently processed subsets using Fourier shell correlation (FSC) (Harauz and van Heel, 1986) with a shaped mask appropriately low-pass-filtered (a proposed protocol for generating the mask is given in Heymann (2018b) and below).
   

Procedure