Group Analysis

CPAC.group_analysis.create_group_analysis(ftest=False, wf_name='groupAnalysis')[source]

FSL FEAT BASED Group Analysis

ftest : boolean, optional(default=False)
Ftest help investigate several contrasts at the same time for example to see whether any of them (or any combination of them) is significantly non-zero. Also, the F-test allows you to compare the contribution of each contrast to the model and decide on significant and non-significant ones
wf_name : string
Workflow name
grp_analysis : workflow object
Group Analysis workflow object

Source

Workflow Inputs:

inputspec.mat_file : string (existing file)
   Mat file containing  matrix for design 

inputspec.con_file : string (existing file)
   Contrast file containing contrast vectors 

inputspec.grp_file : string (existing file)
   file containing matrix specifying the groups the covariance is split into

inputspec.zmap_files : string (existing nifti file)
   derivative or the zmap file for which the group analysis is to be run

inputspec.z_threshold : float
    Z Statistic threshold value for cluster thresholding. It is used to 
    determine what level of activation would be statistically significant. 
    Increasing this will result in higher estimates of required effect.

inputspec.p_threshold : float
    Probability threshold for cluster thresholding.
    
inputspec.fts_file : string (existing file)
   file containing matrix specifying f-contrasts
   
inputspec.paramerters : string (tuple)
    tuple containing which MNI and FSLDIR path information

Workflow Outputs:

outputspec.merged : string (nifti file)
    4D volume file after merging all the derivative 
    files from each specified subject.
    
outputspec.zstats : list (nifti files)
    Z statistic image for each t contrast
    
outputspec.zfstats : list (nifti files)
    Z statistic image for each f contrast

outputspec.fstats : list (nifti files)
    F statistic for each contrast  

outputspec.cluster_threshold : list (nifti files)
   the thresholded Z statistic image for each t contrast

outputspec.cluster_index : list (nifti files)
    image of clusters for each t contrast; the values 
    in the clusters are the index numbers as used 
    in the cluster list.

outputspec.cluster_localmax_txt : list (text files)
    local maxima text file for each t contrast, 
    defines the coordinates of maximum value in the cluster

outputspec.overlay_threshold : list (nifti files)
    3D color rendered stats overlay image for t contrast
    After reloading this image, use the Statistics Color 
    Rendering GUI to reload the color look-up-table

outputspec.overlay_rendered_image : list (nifti files)
   2D color rendered stats overlay picture for each t contrast
    
outputspec.cluster_threshold_zf : list (nifti files)
   the thresholded Z statistic image for each f contrast

outputspec.cluster_index_zf : list (nifti files)
    image of clusters for each f contrast; the values 
    in the clusters are the index numbers as used 
    in the cluster list.
    
outputspec.cluster_localmax_txt_zf : list (text files)
    local maxima text file for each f contrast, 
    defines the coordinates of maximum value in the cluster

outputspec.overlay_threshold_zf : list (nifti files)
    3D color rendered stats overlay image for f contrast
    After reloading this image, use the Statistics Color 
    Rendering GUI to reload the color look-up-table

outputspec.overlay_rendered_image_zf : list (nifti files)
   2D color rendered stats overlay picture for each f contrast

Order of commands:

  • Merge all the Z-map 3D images into 4D image file. For details see fslmerge:

    fslmerge -t sub01/sca/seed1/sca_Z_FWHM_merged.nii 
                sub02/sca/seed1/sca_Z_FWHM.nii.gz ....  
                merge.nii.gz
                
    arguments 
        -t : concatenate images in time
    
  • Create mask specific for analysis. For details see fslmaths:

    fslmaths merged.nii.gz 
            -abs -Tmin -bin mean_mask.nii.gz
    
    arguments 
         -Tmin  : min across time
         -abs   : absolute value
         -bin   : use (current image>0) to binarise
    
  • FSL FLAMEO to perform higher level analysis. For details see flameo:

    flameo --copefile = merged.nii.gz --covsplitfile = anova_with_meanFD.grp --designfile = anova_with_meanFD.mat 
           --fcontrastsfile = anova_with_meanFD.fts --ld=stats --maskfile = mean_mask.nii.gz --runmode=ols 
           --tcontrastsfile = anova_with_meanFD.con
       
    arguments
        --copefile        : cope regressor data file
        --designfile      : design matrix file
        --maskfile        : mask file
        --tcontrastsfile  : file containing an ASCII matrix specifying the t contrasts
        --fcontrastsfile  : file containing an ASCII matrix specifying the f contrasts
        --runmode         : Interference to perform (mixed effects - OLS)
    
  • Run FSL Easy thresh

    Easy thresh is a simple script for carrying out cluster-based thresholding and colour activation overlaying:

    easythresh <raw_zstat> <brain_mask> <z_thresh> <prob_thresh> <background_image> <output_root> [--mm]
    

    A seperate workflow called easythresh is called to run easythresh steps.

High Level Workflow Graph:

workflows/../images/group_analysis.dot.png

Detailed Workflow Graph:

workflows/../images/group_analysis_detailed.dot.png
>>> from group_analysis_preproc import create_group_analysis
>>> preproc = create_group_analysis()
>>> preproc.inputs.inputspec.mat_file = '../group_models/anova_with_meanFD/anova_with_meanFD.mat'
>>> preproc.inputs.inputspec.con_file = '../group_models/anova_with_meanFD/anova_with_meanFD.con'
>>> preproc.inputs.inputspec.grp_file = '../group_models/anova_with_meanFD/anova_with_meanFD.grp'
>>> preproc.inputs.inputspec.zmap_files = ['subjects/sub01/seeds_rest_Dickstein_DLPFC/sca_Z_FWHM.nii.gz', 
                                           'subjects/sub02/seeds_rest_Dickstein_DLPFC/sca_Z_FWHM.nii.gz']
>>> preproc.inputs.inputspec.z_threshold = 2.3
>>> preproc.inputs.inputspec.p_threshold = 0.05
>>> preproc.inputs.inputspec.parameters = ('/usr/local/fsl/', 'MNI152')
>>> preproc.run()  -- SKIP doctest
CPAC.group_analysis.get_operation(in_file)[source]

Method to create operation string for fslmaths

in_file : file
input volume
op_string : string
operation string for fslmaths
IOError
If unable to load the input volume