Hi Lara,



Martin and I discussed your problem today. 

First let us highlight that the problems you are facing to interpret your results are one of the main limitations of this software and the main reason why we have decided to discontinue its development and rather work on an alternative that can provide more meaningful results. This alternative solution would provide beta maps that could make interpretation easier (among other features).

Second, after careful evaluation of the information we have about your experiment, we think you are doing the things right (or as right as possible given the known limitations of the program).

Although imperfect, one can interpret the raw mean maps (MeanDiff) as I explained before, to understand the directionality of your p-values, where negative differences between meanA and meanB will mean meanB is smaller and positive differences will mean meanB is larger. This does not work in your case because you dont have 2 groups but 4 (G1: diag=0 and sex=0, G2: diag=0 and sex=1, G3: diag=1 sex=0, G4: diag=1 and sex=1). In the way the program is encoded only one of the meanA and meanB will be correct, since one will encode diag=1 and sex=1 meaning diag*sex=1 and the other will encode all other groups or diag*sex=0.

Our suggestion is that you generate means and shape difference maps (your own DiffMagnitude maps) that can help you interpret the directionality of your p-value maps better for G3: diag=1 sex=0, G4: diag=1 and sex=1 yourself. After analyzing how all the different Betas in the GLM will interact with each other in the experiment you describe in your commandline, we believe this would be the best thing to do.


SPHARM-PDM includes some commands that will help you do that. Here is the recipe:

1. Generate mean for G3 and G4. For that you will use MeshMath (included in the SPHARM-PDM distribution) 

Commandline: MeshMath subject1_G3.vtk average_output_G3.vtk -avgMesh subject2_G3.vtk ... subjectN_G3.vtk (repeat this for all subjects in G4)

2. Compute distances between avgG3 and avgG4. For that we need to first convert the format of your newly created average_output_G3.vtk and average_output_G4.vtk to Meta format. VTK2Meta is also part of SPHARM.

Commandline: VTK2Meta average_output_G4.vtk average_output_G4.meta (repeat for G3)

Now you compute differences between your two averages using MeshMath:

Commandline: MeshMath average_output_G4.meta -subtract average_output_G3.meta (this will do G3 - G4, meaning if positive differences are computed G4 is bigger than G3 and if negative differences are computed G4 is smaller than G3, you can change the direction by switching the order of your average files in your commandline) 

You will have to rename your output vectors file (mv ./-subtract vectors_G3_to_G4.txt) and also map them into your mean (I usually chose the reference average shape, for example if A-B I will map into A) for visualization in ShapePopulationViewer (MeshMath average_output_G3.vtk average_output_G3_with_attributes.vtk -KWtoPolyData vectors_G3_to_G4.txt vectorMap).

Next step in computation of differences is to compute the signed differences using also MeshMath.

Commandline: MeshMath average_output_G4.meta -magNormDir vectors_G3_to_G4.txt 

Again, you will have to rename your signed distances file (mv ./-magNormDir diffmagnitude_G3_to_G4.txt) and also map them into your mean for visualization in ShapePopulationViewer (MeshMath average_output_G3_with_attributes.vtk average_output_G3_with_attributes.vtk -KWtoPolyData diffmagnitude_G3_to_G4.txt DiffMagnitude).


Load average_output_G3_with_attributes.vtk in ShapePopulationViewer to see a) the vector map named vectorMap, and b) the signed differences in the map named DiffMagnitude. You can choose to change the name of your files or maps to whatever makes sense to you. Finally, let me highlight it is very important to keep the order consistent if you switch the order of the groups to visualize different signs in your maps.



Please, let me know if this makes sense as it comprises a lot of information. I tried to simplify the explanations to make it coherent for you, but if you want me to I can further explain anything that is not clear enough.



I hope that helps.


Best regards,
Beatriz