subtom_cluster

Clusters a motive-list using pre-calculated and supplied coefficients and outputs a classified motive-list and class averages.

This subtomogram classification script uses three MATLAB compiled scripts below:

Options

Directories

scratch_dir: Absolute path to the folder with the input to be processed. Other paths are relative to this one.
local_dir: Absolute path to the folder on a group share, if the scratch directory is cleaned and deleted regularly this can set a local directory to which the important results will be copied. If this is not needed it can be skipped with the option skip_local_copy below.
mcr_cache_dir: Absolute path to MCR directory for the processing.
exec_dir: Directory for executables

Variables

cluster_exec: Cluster executable.
sum_exec: Parallel Summing executable
avg_exec: Final Averaging executable

Memory Options

mem_free: The amount of memory the job requires. This variable determines whether a number of CPUs will be requested to be dedicated for each job. At 24G, one half of the CPUs on a node will be dedicated for each of the processes (12 CPUs). At 48G, all of the CPUs on the node will be dedicated for each of the processes (24 CPUs).
mem_max: The upper bound on the amount of memory the job is allowed to use. If any of the processes request or require more memory than this, the queue will kill the process. This is more of an option for safety of the cluster to prevent the user from crashing the cluster requesting too much memory.

Other Cluster Options

job_name: The job name prefix that will be used for the cluster submission scripts, log files, and error logs for the processing. Be careful that this name is unique because previous submission scripts, logs, and error logs with the same job name prefix will be overwritten in the case of a name collision.
array_max: The maximum number of jobs per cluster submission script. Cluster submission scripts work using the array feature common to queuing systems, and this value is the maximum array size used in a script. If the user requests more batches of processing than this value, then the submission scripts will be split into files of up to array_max jobs.
max_jobs: The maximum number of jobs for alignment. If the number of batches / exceeds this value the script will immediately quit.
run_local: If the user wants to skip the cluster and run the job locally, this value should be set to 1.
skip_local_copy: Set this option to 1 to skip the copying of data to local_dir.

Parallelization Options

iteration: The index of the references to generate : input will be all_motl_fn_prefix_iteration.em (define as integer e.g. iteration=1)
num_avg_batch: The number of batches to split the parallel subtomogram averaging job into.

Subtomogram Classification Workflow Options

Coefficient File Options

coeff_all_motl_fn_prefix: Relative path and name of the concatenated motivelist to cluster and classify.
coeff_fn_prefix: Relative path and name of the coefficients.

Clustering Options

cluster_type: The following determines which algorithm will be used to cluster the determined Eigencoefficients. The valid options are K-means clustering, ‘kmeans’, Hierarchical Ascendent Clustering using a Ward Criterion, ‘hac’, and a Gaussian Mixture Model, ‘gaussmix’.
coeff_idxs: Determines which coefficients are used to cluster. The format should be a semicolon-separated list that also supports ranges with a dash (-), for example 1-5;7;15-19 would select the first five coefficients, the seventh and the fifteenth through the nineteenth for classification. If it is left as “all” all coefficients will be used.
num_classes: How many classes should the particles be clustered into.

Clustering File Options

cluster_all_motl_fn_prefix: Relative path and name of the concatenated motivelist of the output classified particles.

Averaging File Options

ref_fn_prefix: Relative path and name prefix of the reference volumes (e.g. ref_iter.em, the variable will be written as a string e.g. ref_fn_prefix=’sub-directory/ref’)
weight_sum_fn_prefix: Relative path and name prefix of the partial weight files.

Example

scratch_dir="${PWD}"

local_dir=""

mcr_cache_dir="${scratch_dir}/mcr"

exec_dir="XXXINSTALLATION_DIRXXX/bin"

cluster_exec="${exec_dir}/classification/pca/subtom_cluster"

sum_exec="${exec_dir}/classification/pca/subtom_parallel_sums"

avg_exec="${exec_dir}/classification/pca/subtom_weighted_average"

mem_free="1G"

mem_max="64G"

job_name="subTOM"

array_max="1000"

max_jobs="4000"

run_local="0"

skip_local_copy="1"

iteration="1"

num_avg_batch="1"

coeff_all_motl_fn_prefix="combinedmotl/allmotl"

coeff_fn_prefix="class/coeffs"

cluster_type="kmeans"

eig_idxs="all"

num_classes=2

cluster_all_motl_fn_prefix="class/allmotl_class"

ref_fn_prefix="class/ref"

weight_sum_fn_prefix="class/wei"