Generating a starting model

Obtaining a reconstructed density map from a set of particles is an iterative process that requires an initial reference volume, typically a low-resolution reconstruction from the same or a similar sample. When a starting model is not available, one can easily be constructed for icosahedral viruses using the program setup_rmc, which relies on the Random Model Computation (RMC) method.

Assuming that you have already generated a dat subdirectory containing the initial particle parameter files (ending with .dat_000), the simplest procedure is to run three commands

setup_rmc
./RMC_run
./RMC_cleanup

setup_rmc will interrogate the particle parameter files in the parameter directory (default=dat) and setup the directories and scripts required to generate, by default, 10 random models, using 150 images from at least the 3 furthest-from-focus micrographs. It will generate two scripts to run in sequence: RMC_run to launch the random model calculations, and RMC_cleanup to remove all intermediate files after completion. setup_rmc will also construct a minimal auto3dem input file (with suffix _master), that can be used to launch the full reconstruction after the starting model has been obtained.

The number of random models to construct, the number of images to use, and other parameters can be controlled through command line arguments to setup_rmc. Running setup_rmc without any arguments provides a complete list of options. For example, to create 5 random models using 200 images taken from a minimum of 4 micrographs

setup_rmc -nmodels 5 -nimages 200 -nmgmin 4

By default a novel algorithm is used to select the best starting model. In this case all the models are run for the number of iterations specified (default = 10), without calculating the resolution after each iteration. A score based on amplitude statistics is calculated from the radial profile of each model, and the volume with the highest score is selected as starting model. If the resolution-based approach is chosen (-trad flag), at each iteration the resolution is estimated for each model: if the FSC never drops below 0.5 for all spatial frequencies less than 1/25 Å, the calculations are terminated and the current model is designated as the starting model. Otherwise, all calculations are allowed to run to completion, and the best model, according to the FSC resolution estimate, is identified. In either case, the starting model is named rmc.pif and copied to the directory containing the particle parameter files (default = dat). At the end of the calculations, all intermediate files and directories are also moved into a new directory named RMC_temp.

A sample session is shown below:

% ls
dat pif

 
% setup_rmc
[output not shown - enter yes at prompt]

 
% ls
dat           RMC2_master  RMC6_master  RMC_cleanup
pif           RMC3_master  RMC7_master  RMC_logfile_list
RMC10_master  RMC4_master  RMC8_master  RMC_run
RMC1_master   RMC5_master  RMC9_master  Virus_master
 

% ls dat
file1.dat_000  file4.dat_000  file7.dat_000  RMC10  RMC4  RMC7
file2.dat_000  file5.dat_000  file8.dat_000  RMC2   RMC5  RMC8
file3.dat_000  file6.dat_000  RMC1           RMC3   RMC6  RMC9
 

% ./RMC_run

 
% ls
dat  pif  RMC_cleanup  RMC_temp  Virus_master
 

% ls dat
file1.dat_000  file3.dat_000  file5.dat_000  file7.dat_000  rmc.pif
file2.dat_000  file4.dat_000  file6.dat_000  file8.dat_000


% ls RMC_temp
RMC1            RMC2_RESTARTS  RMC5_log       RMC8
RMC10           RMC2_summary   RMC5_master    RMC8_continue
RMC10_continue  RMC3           RMC5_RESTARTS  RMC8_log
RMC10_log       RMC3_continue  RMC5_summary   RMC8_master
RMC10_master    RMC3_log       RMC6           RMC8_RESTARTS
RMC10_RESTARTS  RMC3_master    RMC6_continue  RMC8_summary
RMC10_summary   RMC3_RESTARTS  RMC6_log       RMC9
RMC1_continue   RMC3_summary   RMC6_master    RMC9_continue
RMC1_log        RMC4           RMC6_RESTARTS  RMC9_log
RMC1_master     RMC4_continue  RMC6_summary   RMC9_master
RMC1_RESTARTS   RMC4_log       RMC7           RMC9_RESTARTS
RMC1_summary    RMC4_master    RMC7_continue  RMC9_summary
RMC2            RMC4_RESTARTS  RMC7_log       RMC_bestmap_summary
RMC2_continue   RMC4_summary   RMC7_master    RMC_logfile_list
RMC2_log        RMC5           RMC7_RESTARTS  RMC_run
RMC2_master     RMC5_continue  RMC7_summary
 

% ./RMC_cleanup
 

%ls
dat  pif  Virus_master

If you generate an initial model using the Random Model Computation method, please cite:

Yan X., K. A. Dryden, J. Tang, and T. S. Baker (2007) Ab initio random model method facilitates 3D reconstruction of icosahedral particles. J. Struct. Bio. 157:211-225. (pdf)