MEICA: Difference between revisions

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For the moment please refer to the [https://bitbucket.org/manfredg/me-ica Bitbucket repository] for guidance.
For the moment please refer to the [https://bitbucket.org/manfredg/me-ica Bitbucket repository] for guidance.
<code>
Usage: meica.py [options]                                                                                                               
Options:
  -h, --help            show this help message and exit
  -e TES                ex: -e 14.5,38.5,62.5  Echo times (in ms)
  -d DSINPUTS          ex: -d RESTe1.nii.gz,RESTe2.nii.gz,RESTe3.nii.gz
  -a ANAT              ex: -a mprage.nii.gz  Anatomical dataset (optional)
  -b BASETIME          ex: -b 10s OR -b 10v  Time to steady-state
                        equilibration in seconds(s) or volumes(v). Default 0.
  --MNI                Warp to MNI space using high-resolution template
  Additional processing options:
    --qwarp            Nonlinear anatomical normalization to MNI (or --space
                        template) using 3dQWarp, after affine
    --fres=FRES        Specify functional voxel dim. in mm (iso.) for
                        resampling during preprocessing. Default none. ex:
                        --fres=2.5
    --space=SPACE      Path to specific standard space template for affine
                        anatomical normalization
    --no_skullstrip    Anatomical is already intensity-normalized and skull-
                        stripped (if -a provided)
    --no_despike        Do not de-spike functional data. Default is to de-
                        spike, recommended.
    --no_axialize      Do not re-write dataset in axial-first order. Default
                        is to axialize, recommended.
    --mask_mode=MASK_MODE
                        Mask functional with help from anatomical or standard
                        space images: use 'anat' or 'template'
    --coreg_mode=COREG_MODE
                        Coregistration with Local Pearson and T2* weights
                        (default), or use align_epi_anat.py (edge method): use
                        'lp-t2s' or 'aea'
    --smooth=FWHM      Data FWHM smoothing (3dBlurInMask). Default off. ex:
                        --smooth 3mm
    --align_base=ALIGN_BASE
                        Explicitly specify base dataset for volume
                        registration
    --TR=TR            The TR. Default read from input dataset header
    --tpattern=TPATTERN
                        Slice timing (i.e. alt+z, see 3dTshift -help). Default
                        from header. (N.B. This is important!)
    --align_args=ALIGN_ARGS
                        Additional arguments to anatomical-functional co-
                        registration routine
    --seed=SEED        Seed used for ICA. Default 42.
    --ted_args=TED_ARGS
                        Additional arguments to TE-dependence analysis routine
  Run options:
    --prefix=PREFIX    Prefix for final ME-ICA output datasets.
    --cpus=CPUS        Maximum number of CPUs (OpenMP threads) to use.
                        Default 2.
    --label=LABEL      Label to tag ME-ICA analysis folder.
    --test_proc        Align and preprocess 1 dataset then exit, for testing
    --script_only      Generate script only, then exit
    --pp_only          Preprocess only, then exit.
    --keep_int          Keep preprocessing intermediates. Default delete.
    --skip_check        Skip dependency checks during initialization.
    --OVERWRITE        If meica.xyz directory exists, overwrite.
</code>

Revision as of 18:30, 29 March 2016

More info on how to run MEICA at the BCNI will appear here over the next couple of days.

For the moment please refer to the Bitbucket repository for guidance.

Usage: meica.py [options]

Options:

 -h, --help            show this help message and exit
 -e TES                ex: -e 14.5,38.5,62.5  Echo times (in ms)
 -d DSINPUTS           ex: -d RESTe1.nii.gz,RESTe2.nii.gz,RESTe3.nii.gz
 -a ANAT               ex: -a mprage.nii.gz  Anatomical dataset (optional)
 -b BASETIME           ex: -b 10s OR -b 10v  Time to steady-state
                       equilibration in seconds(s) or volumes(v). Default 0.
 --MNI                 Warp to MNI space using high-resolution template
 Additional processing options:
   --qwarp             Nonlinear anatomical normalization to MNI (or --space
                       template) using 3dQWarp, after affine
   --fres=FRES         Specify functional voxel dim. in mm (iso.) for
                       resampling during preprocessing. Default none. ex:
                       --fres=2.5
   --space=SPACE       Path to specific standard space template for affine
                       anatomical normalization
   --no_skullstrip     Anatomical is already intensity-normalized and skull-
                       stripped (if -a provided)
   --no_despike        Do not de-spike functional data. Default is to de-
                       spike, recommended.
   --no_axialize       Do not re-write dataset in axial-first order. Default
                       is to axialize, recommended.
   --mask_mode=MASK_MODE
                       Mask functional with help from anatomical or standard
                       space images: use 'anat' or 'template'
   --coreg_mode=COREG_MODE
                       Coregistration with Local Pearson and T2* weights
                       (default), or use align_epi_anat.py (edge method): use
                       'lp-t2s' or 'aea'
   --smooth=FWHM       Data FWHM smoothing (3dBlurInMask). Default off. ex:
                       --smooth 3mm
   --align_base=ALIGN_BASE
                       Explicitly specify base dataset for volume
                       registration
   --TR=TR             The TR. Default read from input dataset header
   --tpattern=TPATTERN
                       Slice timing (i.e. alt+z, see 3dTshift -help). Default
                       from header. (N.B. This is important!)
   --align_args=ALIGN_ARGS
                       Additional arguments to anatomical-functional co-
                       registration routine
   --seed=SEED         Seed used for ICA. Default 42.
   --ted_args=TED_ARGS
                       Additional arguments to TE-dependence analysis routine
 Run options:
   --prefix=PREFIX     Prefix for final ME-ICA output datasets.
   --cpus=CPUS         Maximum number of CPUs (OpenMP threads) to use.
                       Default 2.
   --label=LABEL       Label to tag ME-ICA analysis folder.
   --test_proc         Align and preprocess 1 dataset then exit, for testing
   --script_only       Generate script only, then exit
   --pp_only           Preprocess only, then exit.
   --keep_int          Keep preprocessing intermediates. Default delete.
   --skip_check        Skip dependency checks during initialization.
   --OVERWRITE         If meica.xyz directory exists, overwrite.