Can 3DVA be used to quantify the amount of variability?

3D Variability Analysis
1

Hi, not sure if this has been asked before, but is it possible to use 3D variability analysis to quantify the amount of variability in a dataset?

Related to this, are the coordinates along each principal variability component comparable between two different 3DVA jobs (i.e. are the absolute values of the coordinates meaningful)? For example, for one set of particles, the particles are distributed from -100 to +100, but for another set, the particles are distributed from -200 to +200. Is it correct to say that there’s more variability in the second set? Really appreciate any insight/clarification!

2

Hi,

I had the same question, and here’s what I found.

https://guide.cryosparc.com/processing-data/tutorials-and-case-studies/tutorial-3d-variability-analysis-part-one

‘The figure below shows the reaction coordinate distribution of particles, as scatter plots between adjacent pairs of components (0 vs 1, 1 vs 2, 2 vs 3, etc). Clearly, the first component (0) has the most variability. This corresponds to the ratcheting motion of the small subunit.’