PyTom: Classify subtomograms using AC3D


Other than CPCA and MCO, we also have a new classification method: Autofocused Classification for 3D subtomograms (AC3D). AC3D is a clustering algorithm (unsupervised) and its basic idea is to automatically focus the classification on the most variable parts of 3D structures. This new type of similarity score (focused score) enables better discriminative ability.

Please refer to the paper for more details: Autofocused 3D Classification of Cryoelectron Subtomograms, Y. Chen et al., Structure 2014.

Script description

Here we assume you already have the subtomograms aligned, either by template matching or subtomogram alignment.

Subtomogram classification using

This script should be run in parallel:

mpirun -np "numberOfCPUs" pytom PathToPytom/classification/

The parameters are explained below:

And two parameters for controlling the calculation of difference mask.

If you have further questions, please email to: