Thank you very much!

Indeed, I compared results column by column, that was a mistake. I took PCs 
from both datasets and they correlate! )) 

On Tuesday, October 31, 2017 at 6:35:46 PM UTC+3, dcadams wrote:
> Andrey,
> To repeat: there is no reason to expect the numbers to match identically 
> across software packages, particularly column by column (if that is what 
> you are examining). Even if two packages perform things identically in 
> terms of the algebra (e.g,. GPA using TpsRelw and geomorph), the numbers 
> may differ slightly for other reasons (post-rotation of the alignment to 
> the principal axes of the consensus, etc.). 
> What is important for downstream statistical analyses is not the 
> individual columns of numbers found from the GPA alignment, but rather the 
> relationships of specimens in the resultant shape space. That is, how 
> different are shapes from one another? In the case I mentioned above, if 
> you took the aligned specimens from TpsRelw and obtained the Procrustes 
> (Euclidean) distance matrix from them, and did the same with the aligned 
> specimens from geomorph, and then performed a matrix correlation, the 
> correlation would be precisely 1.0.  This means the information is 
> identical in the two superimpositions, even if they differ slightly in how 
> the entire set is oriented relative to the X-Y axis.  Incidentally, in the 
> above case one would also find a perfect correlation between distances from 
> the GPA-aligned specimens, those shapes rotated to their principal axes, or 
> differences in shape found from the thin-plate spline and uniform shape 
> components taken together. For an early discussion of these issues see 
> Rohlf 1999.
> However, performing the procedure above where one set of GPA-aligned 
> coordinates is from MorphoJ will not produce a perfect correlation of 1.0, 
> as MorphoJ uses Full Procrustes superimposition. That means the perceived 
> relationships between shapes is not being represented in the same manner: 
> which of course is a known difference between full and partial Procrustes 
> fitting. How much of a difference one finds between a full and partial 
> Procrustes alignment is dataset dependent.
> Dean

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