Hi,

Many thanks for your prompt reply Pr. Greve.

I did :

mri_glmfit --y 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA/y.mgh 
--fsgd 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA/qdec.fsgd
 dods --glmdir 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA --surf 
fsaverage rh --label 
/home/damien/bin/freesurfer/subjects/fsaverage/label/rh.aparc.label --C 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA/contrasts/rh-Avg-Intercept-area.mat
 --C 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA/contrasts/rh-Diff-dyslexic-control-Intercept-area.mat
 --C 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA/contrasts/rh-Diff-male-female-Intercept-area.mat
 --C 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA/contrasts/rh-X-group-gender-Intercept-area.mat
 --eres-save

mri_segstats --in 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA/eres.mgh 
--sum toto --annot fsaverage rh mc-z.abs.th23.sig.ocn --avgwf 
RH_Dys-CT_CSA_AgeGenderWRCSA.dat


1) I don’t get it though. Probably I made a bad description of my goal, perhaps 
using this terminology of “residuals” also is not very accurate.

I exported the txt file (output of mri_segstats computed on eres.mgh) to a 
statistical software and ran a mancova per cluster on cluster values with 
covariatess : age, right hemispheric surface area + gender factor. I find 
significant effects of the covariates on 7/9 clusters.

I was not expecting such effects. I wanted to extract residuals of surface area 
in the significant clusters obtain using the Qdec Monte Carlo simulation on the 
contrast of interest (Dys - Ct) after removing all covariate effects.

My aim was to look at the differences between the two levels of the factor of 
interest to get a sense of what is happening in this Qdec analysis and this 
particular contrast of interest. These results are in an opposite direction in 
comparison with other Qdec analysis without covariates / ROI analysis on 
surface area residuals after removing effect of gender, age and right 
hemispheric surface area (Destrieux's labels) / Whole-brain VBM analyses with 
covariates (not on surface area then...)

Basically I have the feeling there is something wrong with the contrast display 
in this particular qdec analysis. I don’t know how I could get what I called 
the CSA residuals in the framework of this analysis.


2) Another question: should I standardize or center my covariates before 
proceeding to the analysis?


3) A silly question probably but to be 100% sure… If in the qdec.table.dat, 
order of subjects is first group “ dys “ then second group “ ct “ and that the 
contrast is called: rh-Diff-dys-dyslexic-control-intercept-area , negative p 
value means decrease of surface area in the first group (dys) as compared to 
the second group (ct), right ?


Thank you and best,
Damien MARIE





Douglas Greve 
<http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=from:%22Douglas+Greve%22>
 Wed, 28 Sep 2016 12:40:51 -0700 
<http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=date:20160928>

Those are not residuals. If you want residuals, you will need to run mri_glmfit 
from the command line adding --eres-save. You can get the command line from the 
mri_glmfit.log file in the glmdir





On 9/28/16 10:58 AM, Damien MARIE wrote:
Dear FreeSurfers,
Sorry for the repost. I’m still trying to extract the residuals of cortical 
surface area from a qdec analysis with two factors (2 levels) and 2 covariates.
I tried this command line:
mri_segstats --in 
/home/damien/bin/freesurfer/subjects/qdec/RH_Dys-CT_CSA_AgeGenderWRCSA/y.mgh 
--sum toto --annot fsaverage rh mc-z.abs.th23.sig.ocn --avgwf 
RH_Dys-CT_CSA_AgeGenderWRCSA.dat I’ve got a text file with 9 columns (number of 
clusters) and 69 lines (number of subjects). Now I am not 100% sure it’s really 
the residuals (y.mgh) so I would be glad if somebody could tell me please.
Best,
Damien
Original post:
Dear experts,

I would like to know what is the best and simplest way to extract cortical
surface area and thickness from clusters obtained after a Monte Carlo
correction. This is a group comparison I did with qdec including gender as
discrete variable + age and mean thickness or whole hemispheric surface area as
nuisance factors, so I would like to get the feature residuals after the
removal of the covariate effects.
I am sorry, I saw several posts about that but for me it’s not completely clear
what command line I should use to get tables for this…

Thank you and best,
Damien




*Damien MARIE*

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