|
Size: 2269
Comment:
|
Size: 2773
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 3: | Line 3: |
| == Run mris_glm to compute contrast == | == Group Analysis command lines == |
| Line 5: | Line 5: |
| Follow these steps to run mris_glm for computing contrasts: | In order to compute the contrats you will first need to change to the tutorial data directory and setup SUBJECTS_DIR: |
| Line 8: | Line 8: |
| # change to the tutorial data directory and setup SUBJECTS_DIR: cd $FREESURFER_HOME/subjects/buckner_public_distribution/FsTutorialDataSet/group_analysis_tutorial |
cd $FREESURFER_HOME/subjects/buckner_data/tutorial_subjs/group_analysis_tutorial |
| Line 11: | Line 10: |
| }}} Change into the directory you ran the estimation step in, most likely called 'stats': {{{ |
|
| Line 14: | Line 18: |
| Upon successful completion of the estimation step (computed in a prior exercise), mris_glm may be configured on command line with proper options to perform contrast computation: | Upon successful completion of the make_average_subject command you should have an average subject in your SUBJECTS_DIR. After successfully completing [wiki:Self:FsTutorial/CreateFsgdFile Exercise A.] and [wiki:Self:FsTutorial/CreateContrastVectors Exercise B.] you should have an FSGD file called my_gender_age.txt and a contrast file called age.mat, both in your SUBJECTS_DIR/stats directory . The following are sample commands, that can be used with the data, to complete a group analysis: |
| Line 17: | Line 22: |
| mris_glm --hemi lh \ --trgsubj average \ --fsgd ./my_gender_age_fsgd.txt doss \ --beta_in ./beta_doss-thickness-100lh bfloat \ --var_in ./var_doss-thickness-100lh.w paint \ --gcv 0 0 1 \ --ces ./ces_Age_doss-thickness-100lh.w paint \ --t ./t_Age_doss-thickness-100lh.w paint \ --sigt ./sigt_Age_doss-thickness-100lh.w paint |
mris_preproc --fsgd my_gender_age.txt --target average --hemi lh --meas thickness --out lh.my_gender_age.thickness.mgh |
| Line 27: | Line 25: |
Once this completes you should see the file lh.my_gender_age.thickness.mgh. The next step, the smoothing step, will use this as input: |
|
| Line 28: | Line 30: |
| # For the right hemisphere mris_glm --hemi rh \ --trgsubj average \ --fsgd ./my_gender_age_fsgd.txt doss \ --beta_in ./beta_doss-thickness-100rh bfloat \ --var_in ./var_doss-thickness-100rh.w paint \ --gcv 0 0 1 \ --ces ./ces_Age_doss-thickness-100rh.w paint \ --t ./t_Age_doss-thickness-100rh.w paint \ --sigt ./sigt_Age_doss-thickness-100rh.w paint |
mri_surf2surf --hemi lh --s average --sval lh.my_gender_age.thickness.mgh --fwhm 10 --tval lh.my_gender_age.thickness.10.mgh |
| Line 39: | Line 32: |
| With the above configuration, mris_glm tests the given subjects for straight correlation between thickness and age. The command will read in the regression coefficients (--beta_in) and noise variance (--var_in) that were generated from the estimation process, and save the contrast effect size (ces), t-ratio of the contrast, and the significance of the t-ratio (i.e., t-test) in the same directory, all in paint format. | |
| Line 41: | Line 33: |
| Upon completion, make sure that the following files are available in the directory from which mris_glm was run by typing: | Once this is complete you should see the file lh.my_gender_age.thickness.10.mgh. The next step will test the hypothesis you've set up using your contrast vector: |
| Line 43: | Line 36: |
| ls -l ces_Age_doss-thickness-100lh.w ls -l t_Age_doss-thickness-100lh.w ls -l sigt_Age_doss-thickness-100lh.w |
mri_glmfit --y lh.my_gender_age.thickness.10.mgh --fsgd my_gender_age.txt doss --glmdir lh.my_gender_age.glmdir --pca --surf --average lh --C age.mat }}} |
| Line 47: | Line 39: |
| ls -l ces_Age_doss-thickness-100rh.w ls -l t_Age_doss-thickness-100rh.w ls -l sigt_Age_doss-thickness-100rh.w |
You should have two new directories in FREESURFER_HOME/subjects/buckner_data/tutorial_subjs/group_analysis_tutorial/stats - lh.my_gender_age.glmdir and rh.my_gender_age.glmdir. If you do: {{{ ls lh.my_gender_age.glmdir |
| Line 51: | Line 45: |
| in that directory. | |
| Line 53: | Line 46: |
| you should see this: {{{ age/ beta.mgh fsgd.X.mat pca-eres/ rvar.mgh y.fsgd ar1.mgh eres.mgh mri_glmfit.log rstd.mgh Xg.dat }}} and if you do: {{{ ls lh.my_gender_age.glmdir/age }}} you should see this: {{{ C.dat F.mgh gamma.mgh maxvox.dat sig.mgh }}} You can view your results by opening the average subject in tksurfer: {{{ tksurfer average lh inflated }}} and loading in your overlay, '''File -> Load Overlay''' and browse to stats/lh.my_gender_age.glmdir/age/sig.mgh. If you would like to also view the scatter plots associated with this you can do so by '''File -> Load Group Descriptor File''' and browse to stats/lh.my_gender_age.glmdir/y.fsgd. The commands are the same for the right hemisphere, replacing every '''lh''' with an '''rh'''. |
[wiki:FsTutorial top] | [wiki:FsTutorial/GroupAnalysis previous]
Group Analysis command lines
In order to compute the contrats you will first need to change to the tutorial data directory and setup SUBJECTS_DIR:
cd $FREESURFER_HOME/subjects/buckner_data/tutorial_subjs/group_analysis_tutorial
setenv SUBJECTS_DIR ${PWD}Change into the directory you ran the estimation step in, most likely called 'stats':
cd stats
Upon successful completion of the make_average_subject command you should have an average subject in your SUBJECTS_DIR. After successfully completing [wiki:FsTutorial/CreateFsgdFile Exercise A.] and [wiki:FsTutorial/CreateContrastVectors Exercise B.] you should have an FSGD file called my_gender_age.txt and a contrast file called age.mat, both in your SUBJECTS_DIR/stats directory . The following are sample commands, that can be used with the data, to complete a group analysis:
# For the left hemisphere mris_preproc --fsgd my_gender_age.txt --target average --hemi lh --meas thickness --out lh.my_gender_age.thickness.mgh
Once this completes you should see the file lh.my_gender_age.thickness.mgh. The next step, the smoothing step, will use this as input:
mri_surf2surf --hemi lh --s average --sval lh.my_gender_age.thickness.mgh --fwhm 10 --tval lh.my_gender_age.thickness.10.mgh
Once this is complete you should see the file lh.my_gender_age.thickness.10.mgh. The next step will test the hypothesis you've set up using your contrast vector:
mri_glmfit --y lh.my_gender_age.thickness.10.mgh --fsgd my_gender_age.txt doss --glmdir lh.my_gender_age.glmdir --pca --surf --average lh --C age.mat
You should have two new directories in FREESURFER_HOME/subjects/buckner_data/tutorial_subjs/group_analysis_tutorial/stats - lh.my_gender_age.glmdir and rh.my_gender_age.glmdir. If you do:
ls lh.my_gender_age.glmdir
you should see this:
age/ beta.mgh fsgd.X.mat pca-eres/ rvar.mgh y.fsgd ar1.mgh eres.mgh mri_glmfit.log rstd.mgh Xg.dat
and if you do:
ls lh.my_gender_age.glmdir/age
you should see this:
C.dat F.mgh gamma.mgh maxvox.dat sig.mgh
You can view your results by opening the average subject in tksurfer:
tksurfer average lh inflated
and loading in your overlay, File -> Load Overlay and browse to stats/lh.my_gender_age.glmdir/age/sig.mgh. If you would like to also view the scatter plots associated with this you can do so by File -> Load Group Descriptor File and browse to stats/lh.my_gender_age.glmdir/y.fsgd.
The commands are the same for the right hemisphere, replacing every lh with an rh.