Local Refinement

Local Refinement and Particle Subtraction are two jobs useful in addressing the issue of sample flexibility, along with 3D Variability and Non-Uniform Refinement.

Local Refinement is the process of iteratively refining a selected sub-volume within a larger volume, while also providing a characterization of the conformational distribution that is represented in the particle images. The primary use of Local Refinement is to account for and "undo" the relative motion between the masked sub-volume, and the rest of the molecule, which differentiates Local Refinement from other jobs like Non-Uniform Refinement.

Particle Subtraction is a useful job in preparing particles for the local refinement job. Particle Subtraction involves subtracting the signal, contributed to by the rest of the molecule, from the input particle images. This yields a set of particle images containing the signal only from the masked sub-volume. Often, using signal-subtracted particles instead of the raw particles may improve alignment during Local Refinement, and hence improve the quality of the refinement.

Also included in this section is a tutorial on Mask Selection and Generation in UCSF Chimera, which details how to take a consensus refinement and generate masks covering the region of interest (for Local Refinement), as well as the inverse region (for Particle Subtraction).