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PennLINC / qsiprep

Preprocessing of diffusion MRI
http://qsiprep.readthedocs.io
BSD 3-Clause "New" or "Revised" License
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Missing dependencies in v 16 0rc3 #448

Closed bdeck8317 closed 2 years ago

bdeck8317 commented 2 years ago

Hey there,

Attempting to run singularity container of QSIprep v 16 0rc3

Check out the following errors with the dependencies. 

Commandline: module load singularity
Running task 1
Commandline: singularity run qsiprep_160rc3.sif 10527bids_data/ 10527qsiprep_out/ participant --participant_label 10527 --output-resolution 1.3 --dwi_denoise_window auto --denoise-method dwidenoise --unringing-method mrdegibbs --distortion-group-merge none --output-space T1w --template MNI152NLin2009cAsym --b0-to-t1w-transform Affine --b0-motion-corr-to iterative --hmc-transform Affine --hmc_model eddy --shoreline_iters 2 --skull-strip-template OASIS --fs-license-file license.txt --do-reconall -w 10527tmpdir/
        1: [WARN] The recommended file /README is missing. See Section 03 (Modality agnostic files) of the BIDS specification. (code: 101 - README_FILE_MISSING)

        Please visit https://neurostars.org/search?q=README_FILE_MISSING for existing conversations about this issue.

        Summary:                  Available Tasks:        Available Modalities: 
        42 Files, 324.31MB        bart                    T1w                   
        1 - Subject               bht                     dwi                   
        1 - Session               pamret                  bold                  
                                  pamenc                  events                
                                  rest                    physio                
                                  stopsignal                                    
                                  scap                                          
                                  taskswitch                                    

        If you have any questions, please post on https://neurostars.org/tags/bids.

Making sure the input data is BIDS compliant (warnings can be ignored in most cases).
220729-22:11:00,332 nipype.workflow INFO:
         Running with omp_nthreads=8, nthreads=16
220729-22:11:00,336 nipype.workflow IMPORTANT:

    Running qsiprep version 0.16.0RC3:
      * BIDS dataset path: /home/bdeck8317_gmail_com/10527bids_data.
      * Participant list: ['10527'].
      * Run identifier: 20220729-221059_05343a3d-7ae1-4207-b896-f4f77265b9d2.

220729-22:11:00,840 nipype.utils WARNING:
         A newer version (1.8.3) of nipy/nipype is available. You are using 1.8.1
220729-22:11:01,683 nipype.workflow INFO:
         Combining all 1 dwis within the single available session
220729-22:11:01,691 nipype.workflow INFO:
         [{'dwi_series': ['/home/bdeck8317_gmail_com/10527bids_data/sub-10527/dwi/sub-10527_dwi.nii.gz'], 'fieldmap_info': {'suffix': None}, 'dwi_series_pedir': 'j-', 'concatenated_bids_name': 'sub-10527'}]
220729-22:11:01,745 nipype.workflow IMPORTANT:
         Creating dwi processing workflow "dwi_preproc_wf" to produce output sub-10527 (1.04 GB / 75 DWIs). Memory resampled/largemem=1.15/1.19 GB.
220729-22:11:01,747 nipype.workflow INFO:
         Automatically using 5, 5, 5 window for dwidenoise
220729-22:11:01,764 nipype.workflow INFO:
         Using 8 threads in eddy
220729-22:11:04,80 nipype.workflow IMPORTANT:
         Works derived from this qsiprep execution should include the following boilerplate:

Preprocessing was performed using *QSIPrep* 0.16.0RC3,
which is based on *Nipype* 1.8.1
(@nipype1; @nipype2; RRID:SCR_002502).

Anatomical data preprocessing

: The T1-weighted (T1w) image was corrected for intensity non-uniformity (INU)
using `N4BiasFieldCorrection` [@n4, ANTs 2.3.1],
and used as T1w-reference throughout the workflow.
The T1w-reference was then skull-stripped using `antsBrainExtraction.sh`
(ANTs 2.3.1), using OASIS as target template.
Brain surfaces were reconstructed using `recon-all` [FreeSurfer 6.0.1,
RRID:SCR_001847, @fs_reconall], and the brain mask estimated
previously was refined with a custom variation of the method to reconcile
ANTs-derived and FreeSurfer-derived segmentations of the cortical
gray-matter of Mindboggle [RRID:SCR_002438, @mindboggle].
Spatial normalization to the ICBM 152 Nonlinear Asymmetrical
template version 2009c [@mni, RRID:SCR_008796] was performed
through nonlinear registration with `antsRegistration`
[ANTs 2.3.1, RRID:SCR_004757, @ants], using
brain-extracted versions of both T1w volume and template.
Brain tissue segmentation of cerebrospinal fluid (CSF),
white-matter (WM) and gray-matter (GM) was performed on
the brain-extracted T1w using `FAST` [FSL 6.0.5.1:57b01774, RRID:SCR_002823,
@fsl_fast].

Diffusion data preprocessing

: Any images with a b-value less than 100 s/mm^2 were treated as a *b*=0 image. MP-PCA denoising as implemented in MRtrix3's `dwidenoise`[@dwidenoise1] was applied with a 5-voxel window. After MP-PCA, Gibbs unringing was performed using MRtrix3's `mrdegibbs` [@mrdegibbs]. Following unringing, B1 field inhomogeneity was corrected using `dwibiascorrect` from MRtrix3 with the N4 algorithm [@n4]. After B1 bias correction, the mean intensity of the DWI series was adjusted so all the mean intensity of the b=0 images matched across eachseparate DWI scanning sequence.

FSL (version 6.0.5.1:57b01774)'s eddy was used for head motion correction and Eddy current correction [@anderssoneddy]. Eddy was configured with a $q$-space smoothing factor of 10, a total of 5 iterations, and 1000 voxels used to estimate hyperparameters. A linear first level model and a linear second level model were used to characterize Eddy current-related spatial distortion. $q$-space coordinates were forcefully assigned to shells. Field offset was attempted to be separated from subject movement. Shells were aligned post-eddy. Eddy's outlier replacement was run [@eddyrepol]. Data were grouped by slice, only including values from slices determined to contain at least 250 intracerebral voxels. Groups deviating by more than 4 standard deviations from the prediction had their data replaced with imputed values. Final interpolation was performed using the `jac` method.

Several confounding time-series were calculated based on the
preprocessed DWI: framewise displacement (FD) using the
implementation in *Nipype* [following the definitions by @power_fd_dvars].
The head-motion estimates calculated in the correction step were also
placed within the corresponding confounds file. Slicewise cross correlation
was also calculated.
The DWI time-series were resampled to ACPC,
generating a *preprocessed DWI run in ACPC space* with 1.3mm isotropic voxels.

Many internal operations of *QSIPrep* use
*Nilearn* 0.9.1 [@nilearn, RRID:SCR_001362] and
*Dipy* [@dipy].
For more details of the pipeline, see [the section corresponding
to workflows in *QSIPrep*'s documentation](https://qsiprep.readthedocs.io/en/latest/workflows.html "QSIPrep's documentation").

### References

[WARNING] This document format requires a nonempty <title> element.
  Please specify either 'title' or 'pagetitle' in the metadata.
  Falling back to 'CITATION'
Cannot run qsiprep. Missing dependencies:
        mri_label2vol (Interface: Label2Vol)
        mri_label2vol (Interface: Label2Vol)
        mri_convert (Interface: MRIConvert)
        mri_convert (Interface: MRIConvert)
        mris_convert (Interface: MRIsConvert)
        mris_expand (Interface: MakeMidthickness)
        recon-all (Interface: ReconAll)
        recon-all (Interface: ReconAll)
        recon-all (Interface: ReconAll)
        recon-all (Interface: ReconAll)
        recon-all (Interface: ReconAllRPT)

A note, this issue only occurs if the user supplies the --do-reconall flag. Otherwise, Freesurfer is not loaded and QSIprep v 16.0RC3 runs properly.

bdeck8317 commented 2 years ago

duplication of #384, sorry about that!