Usefulaf: An all-in-one - Docker/Singularity image for single-cell processing with alevin-fry
+ readme: 'Usefulaf: + An all-in-one Docker/Singularity image for single-cell processing with alevin-fry
Alevin-fry is a fast,
accurate, and memory-frugal tool for preprocessing single-cell and single-nucleus
@@ -12365,141 +12365,141 @@ Characterisation-Virtual-Laboratory/CharacterisationVL-Software:
data_format: 2
description: null
filenames:
- - vscode/Singularity.vscode_1.39.2
+ - jupyter-ml/Singularity.jupyter-ml_20201120
+ - jupyter-ml/Singularity.jupyter-ml_20210415
+ - ariba/Singularity.ariba_2.12.1
+ - ariba/Singularity.ariba_2.14.4
+ - ccp-em/Singularity.ccp-em_v1.3.0-cuda-9.0
+ - ccp-em/Singularity.ccp-em_nightly-20210608-cuda-9.0
+ - chimera/Singularity.chimera_v1.10.2-cuda10.1
+ - chimera/Singularity.chimera_v1.11-cuda10.1
+ - chimera/Singularity.chimera_v1.14-cuda10.1
+ - chimera/Singularity.chimera_v1.13-cuda10.1
+ - apex/Singularity.apex_master
+ - cvmfs-client/Singularity.cvmfs-client
+ - dtsa2/Singularity.dtsa2
+ - mydata-python/Singularity.mydata-python_20200603
- imod/Singularity.imod_v4_11_15
- - bids-validator/Singularity.bids-validator-1.3.1
- - bids-validator/Singularity.bids-validator-1.2.2
- - libertem/Singularity.libertem-0.7.0
- - libertem/Singularity.libertem-0.10.0
- - libertem/Singularity.libertem-0.4.0
- - libertem/Singularity.libertem-0.9.0
- - libertem/Singularity.libertem-0.11.0
- - libertem/Singularity.libertem-0.5.1
- - libertem/Singularity.libertem-0.5.0
- - libertem/Singularity.libertem-0.8.0
- - libertem/Singularity.libertem-0.2.2
- - libertem/Singularity.libertem-0.4.1
- - libertem/Singularity.libertem-0.6.0
- - deeplabcut/Singularity.latest
- - ants/Singularity.ants_2.3.4
- - ants/Singularity.ants_2.3.1
- - nanconvert/Singularity.nanconvert
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- - argos/Singularity.argos_3.0.0-beta53
- - protomo/Singularity.protomo-2.4.2
- - fsl/Singularity.fsl
- - cistem/Singularity.cisTEM-1.0.0-beta
- gimp/Singularity.gimp_2.8.22
- gimp/Singularity.gimp_2.8
- - imagemagick/Singularity.imagemagick-7.0.8-68
- - pyprismatic/Singularity.pyprismatic_1_2_1-cuda-11.0
- - graphviz/Singularity.graphviz-2.40.1
- - mrtrix3tissue/Singularity.mrtrix3tissue-5.2.8
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- - apex/Singularity.apex_master
- - cvmfs-client/Singularity.cvmfs-client
- - 3dslicer/Singularity.3dslicer_4.10.2
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- - mydata/Singularity.mydata_0.9.2-1
- - ariba/Singularity.ariba_2.14.4
- - ariba/Singularity.ariba_2.12.1
- - matlab/Singularity.MATLAB_SAMPLE
- - eman/Singularity.eman_2.9
- - eman/Singularity.eman_2.22
+ - scipoptsuite/Singularity.scipoptsuite-8.0.0_sh
+ - scipoptsuite/Singularity.scipoptsuite-7.0.3_sh
+ - eman/Singularity.eman_2.3.1
- eman/Singularity.eman_2.3
- eman/Singularity.eman_2.91
- - eman/Singularity.eman_2.3.1
- - dragondisk/Singularity.dragondisk_v1_0_5
- - dristhi/Singularity.dristhi_2.7
- - meshlab/Singularity.meshlab
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- - anaconda3/Singularity.anaconda3_5.3.0-cuda-11.0.3
- - x2goclient/Singularity.x2goclient_latest
- - jupyter-ml/Singularity.jupyter-ml_20210415
- - jupyter-ml/Singularity.jupyter-ml_20201120
- - digitalmicrograph-free/Singularity.digitalmicrograph-free_2.32.888.0
- - ubuntu-base-image/Singularity.1804-cuda9
- - ubuntu-base-image/Singularity.1804
- - ubuntu-base-image/Singularity.2004
- - ubuntu-base-image/Singularity.2004-cuda11.5
- - ubuntu-base-image/Singularity.1804-cuda10.1
- - ubuntu-base-image/Singularity.2004-cuda11.0
+ - eman/Singularity.eman_2.9
+ - eman/Singularity.eman_2.22
+ - nanconvert/Singularity.nanconvert
+ - mib/Singularity.mib_2.511
- mantid/Singularity.mantid_v_3_13_0
- - ashs/Singularity.ashs_2.0.0
- - datalad/Singularity.datalad_0.13.3
- - quit/Singularity.quit_2.0.2
- - omero.insight/Singularity.omero_5.5.10
- - mydata-python/Singularity.mydata-python_20200603
- - dtsa2/Singularity.dtsa2
- - cellprofiler/Singularity.cellprofiler_3.1.9
- - cellprofiler/Singularity.cellprofiler_3.1.5
- - crisprcas/Singularity.crisprcas
- - jmrui/Singularity.jmrui_5.2
- - darknet/Singularity.darknet_yolo_v3-cuda-9.0
- - paraview/Singularity.paraview_5.6.0-cuda-9.0
- - openrefine/Singularity.openrefine-3.1
- - mango/Singularity.mango_4.0.1
+ - mydata/Singularity.mydata_0.9.2-1
+ - connectome-workbench/Singularity.connectome-workbench_1.4.2
+ - mytardisclient/Singularity.mytardisclient_20200603
- ilastik/Singularity.ilastik_1.3.3post3
- - caffe-unet/Singularity.caffe-unet_1.0
- - imagej/Singularity.imagej_1.50e
- - amide/Singularity.amide-1.0.5
+ - globus-cli/Singularity.globus-cli-v2.0.0
+ - cryolo/Singularity.cryolo_v1_6_1
+ - cryolo/Singularity.cryolo_v1_5_6
+ - cryolo/Singularity.ubuntu-cryyolo
+ - cryolo/Singularity.cryolo_v1_0_0
+ - cryolo/Singularity.cryolo_v1_0_4
- bidscoin/Singularity.bidscoin_3
- - relion/Singularity.relion_4.0
- - relion/Singularity.relion_3.0.7
- - relion/Singularity.relion_3.1.3
- - relion/Singularity.relion_3.1_beta
- - relion/Singularity.relion_3.1.0
- - git-annex/Singularity.git-annex.6.20180227
- - chimerax/Singularity.chimerax-v0.8-cuda9
- - chimerax/Singularity.chimerax-v0.6-cuda9
+ - octave/Singularity.octave
+ - octave/Singularity.octave-4.2.2
+ - cellprofiler/Singularity.cellprofiler_3.1.5
+ - cellprofiler/Singularity.cellprofiler_3.1.9
+ - paraview/Singularity.paraview_5.6.0-cuda-9.0
+ - dke/Singularity.dke
- haystack/Singularity.haystack_bio-0.5.0
- haystack/Singularity.haystack_bio-0.5.5
- - colmap/Singularity.colmap_3.5
- - colmap/Singularity.colmap_3.6-dev.3
- - connectome-workbench/Singularity.connectome-workbench_1.4.2
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- - chimera/Singularity.chimera_v1.10.2-cuda10.1
- - chimera/Singularity.chimera_v1.11-cuda10.1
- - chimera/Singularity.chimera_v1.14-cuda10.1
- - chimera/Singularity.chimera_v1.13-cuda10.1
- - dke/Singularity.dke
- - mrtrix/Singularity.mrtrix-3.0.1
- - mrtrix/Singularity.mrtrix-3.0.2
+ - fsl/Singularity.fsl
+ - argos/Singularity.argos_3.0.0-beta52
+ - argos/Singularity.argos_3.0.0-beta53
+ - R/Singularity.R_4.0.5
+ - bids-validator/Singularity.bids-validator-1.3.1
+ - bids-validator/Singularity.bids-validator-1.2.2
+ - openrefine/Singularity.openrefine-3.1
+ - fiji/Singularity.fiji
- mrtrix/Singularity.mrtrix_3_beta
+ - mrtrix/Singularity.mrtrix-3.0.1
- mrtrix/Singularity.mrtrix-3.0.0
+ - mrtrix/Singularity.mrtrix-3.0.2
- mrtrix/Singularity.mrtrix-3.0.3
- - ccp-em/Singularity.ccp-em_nightly-20210608-cuda-9.0
- - ccp-em/Singularity.ccp-em_v1.3.0-cuda-9.0
+ - caffe/Singularity.caffe_1.0
+ - 3dslicer/Singularity.3dslicer_4.8.1
+ - 3dslicer/Singularity.3dslicer_4.10.2
+ - chimerax/Singularity.chimerax-v0.8-cuda9
+ - chimerax/Singularity.chimerax-v0.6-cuda9
+ - mrtrix3tissue/Singularity.mrtrix3tissue-5.2.8
+ - mrtrix3tissue/Singularity.mrtrix3tissue-5.2.9-cuda10.1
+ - omero.insight/Singularity.omero_5.5.10
+ - darknet/Singularity.darknet_yolo_v3-cuda-9.0
+ - deeplabcut/Singularity.latest
+ - ubuntu-base-image/Singularity.1804
+ - ubuntu-base-image/Singularity.1804-cuda10.1
+ - ubuntu-base-image/Singularity.2004
+ - ubuntu-base-image/Singularity.2004-cuda11.0
+ - ubuntu-base-image/Singularity.1804-cuda9
+ - ubuntu-base-image/Singularity.2004-cuda11.5
+ - volview/Singularity.VolView_3.4-cuda-9.0
+ - volview/Singularity.volview
+ - colmap/Singularity.colmap_3.5
+ - colmap/Singularity.colmap_3.6-dev.3
- atom/Singularity.atom_1.39.1
- atom/Singularity.atom_1.45.0
- - globus-connect-personal/Singularity.globus-connect-personal_latest
- - caffe/Singularity.caffe_1.0
- - openmodelica/Singularity.openmodelica_1.14.2-cuda-10.1
- - imblproc/Singularity.imblproc
- - globus-cli/Singularity.globus-cli-v2.0.0
- - octopus/Singularity.octopus
+ - meshlab/Singularity.meshlab
+ - octopus/Singularity.octopus_11.4_parallel
- octopus/Singularity.octopus_11.4
+ - octopus/Singularity.octopus
- octopus/Singularity.octopus_8.4_parallel
- - octopus/Singularity.octopus_11.4_parallel
- octopus/Singularity.octopus_8.4
- - octave/Singularity.octave
- - octave/Singularity.octave-4.2.2
- - omero-insight/Singularity.1804
- - scipoptsuite/Singularity.scipoptsuite-7.0.3_sh
- - scipoptsuite/Singularity.scipoptsuite-8.0.0_sh
+ - imagemagick/Singularity.imagemagick-7.0.8-68
- cloudstor/Singularity.cloudstor-2.4.1
- - volview/Singularity.VolView_3.4-cuda-9.0
- - volview/Singularity.volview
- - cryolo/Singularity.cryolo_v1_5_6
- - cryolo/Singularity.ubuntu-cryyolo
- - cryolo/Singularity.cryolo_v1_6_1
- - cryolo/Singularity.cryolo_v1_0_0
- - cryolo/Singularity.cryolo_v1_0_4
- - R/Singularity.R_4.0.5
- - mib/Singularity.mib_2.511
- - fiji/Singularity.fiji
+ - amide/Singularity.amide-1.0.5
+ - jmrui/Singularity.jmrui_5.2
+ - relion/Singularity.relion_4.0
+ - relion/Singularity.relion_3.1_beta
+ - relion/Singularity.relion_3.0.7
+ - relion/Singularity.relion_3.1.0
+ - relion/Singularity.relion_3.1.3
+ - imagej/Singularity.imagej_1.50e
+ - pyprismatic/Singularity.pyprismatic_1_2_1-cuda-11.0
+ - ants/Singularity.ants_2.3.4
+ - ants/Singularity.ants_2.3.1
+ - globus-connect-personal/Singularity.globus-connect-personal_latest
+ - dragondisk/Singularity.dragondisk_v1_0_5
+ - omero-insight/Singularity.1804
+ - quit/Singularity.quit_2.0.2
+ - matlab/Singularity.MATLAB_SAMPLE
+ - openmodelica/Singularity.openmodelica_1.14.2-cuda-10.1
+ - crisprcas/Singularity.crisprcas
+ - protomo/Singularity.protomo-2.4.2
+ - libertem/Singularity.libertem-0.8.0
+ - libertem/Singularity.libertem-0.5.0
+ - libertem/Singularity.libertem-0.11.0
+ - libertem/Singularity.libertem-0.4.0
+ - libertem/Singularity.libertem-0.4.1
+ - libertem/Singularity.libertem-0.5.1
+ - libertem/Singularity.libertem-0.2.2
+ - libertem/Singularity.libertem-0.6.0
+ - libertem/Singularity.libertem-0.7.0
+ - libertem/Singularity.libertem-0.10.0
+ - libertem/Singularity.libertem-0.9.0
+ - digitalmicrograph-free/Singularity.digitalmicrograph-free_2.32.888.0
+ - x2goclient/Singularity.x2goclient_latest
+ - datalad/Singularity.datalad_0.13.3
- cytoscape/Singularity.cytoscape_3.8.0
+ - imblproc/Singularity.imblproc
+ - anaconda3/Singularity.anaconda3_5.3.0
+ - anaconda3/Singularity.anaconda3_5.3.0-cuda-11.0.3
+ - cistem/Singularity.cisTEM-1.0.0-beta
+ - graphviz/Singularity.graphviz-2.40.1
+ - jupyter-fileuploadtool/Singularity.jupyter-fileuploadtool_20201211
+ - dristhi/Singularity.dristhi_2.7
+ - caffe-unet/Singularity.caffe-unet_1.0
+ - mango/Singularity.mango_4.0.1
+ - ashs/Singularity.ashs_2.0.0
+ - git-annex/Singularity.git-annex.6.20180227
+ - vscode/Singularity.vscode_1.39.2
full_name: Characterisation-Virtual-Laboratory/CharacterisationVL-Software
latest_release: null
readme: "Usefulaf
is an all-in-one Docker/Singularity image for single-cell processing with Alevin-fry(
- Usefulaf history
+ Usefulaf
+ history
\nmutect-nfPreQual (dtiQA v7 Multi) User\
- \ Guide
Contents
\n\n
\n
PreQual (dtiQA v7 Multi) User Guide
\nContents
\n- \n\
+
- Overview \n
- Authors and Reference \n
- Getting Started \n\ +
- Containerization of Source Code \n\ +
- Command \n
- Arguments\ + \ and I/O \n
- Configuration File \n\ +
- Examples \n
- Running BIDS Data \n
- Options \n
- Pipeline Processing Steps \n
- Pipeline Quality Assurance Steps \n\
- Outputs \n
- Note on Versioning for VUIIS XNAT Users \n
Overview
\nNote on Versioning for VUIIS XNAT Users\n\n
Overview
\n![\"Pipeline](\"https://github.com/MASILab/PreQual/blob/master/overview.png?raw=true\"\)
- \n
- \n\
Summary: Perform integrated preprocessing and quality assurance\ @@ -36488,11 +36488,11 @@ MASILab/PreQual: \ applicable)
\n - Analysis of gradient nonlinear fields (if applicable) \n\
- Verification of intra-pipeline masking \n
- Analysis of tensor goodness-of-fit \n\
- Voxel-wise and region-wise quantification of FA \n
- Voxel-wise quantification\ - \ of MD \n\n\n
\n\
- Leon Y. Cai, Qi Yang, Colin\ - \ B. Hansen, Vishwesh Nath, Karthik Ramadass, Graham W. Johnson, Benjamin N. Conrad,\ + \ of MD\n\n\n\n
Authors and Reference
\nMedical-image Analysis and Statistical\ \ Interpretation (MASI) Lab, Vanderbilt University, Nashville, TN, USA
\n\ -Getting Started
\nThe PreQual software is designed to run inside\ - \ a Singularity container. The\ - \ container requires an \"inputs\" folder that\ - \ holds all required input diffusion image files (i.e., .nii.gz, .bval, and .bvec\ - \ files) and a configuration file. For those\ - \ running Synb0-DisCo to correct susceptibility distortions without reverse phase-encoded\ - \ images, this folder will also contain the structural\ - \ T1 image. The container also requires an \"outputs\" folder that will hold all the outputs after the pipeline runs.\ - \ We also need to know the image axis\ - \ on which phase encoding was performed for all inputs (i.e., \"i\" for the first\ - \ dimension, \"j\" for the second). To build the configuration file, we need to\ - \ know the direction along said axis\ - \ in which each image was phase encoded (i.e., \"+\" for positive direction and\ - \ \"-\" for the negative direction) and the readout\ - \ time for each input image. Once we have this information, we bind the inputs\ - \ and outputs directories into the container to run the pipeline.
\n\ -Note: The phase encoding axis, direction, and readout time must be known ahead\ - \ of time, as this information is not stored in NIFTI headers. Depending on the\ - \ scanner used, they may be available in JSON sidecars when NIFTIs are converted\ - \ from DICOMs with dcm2niix.
\nContainerization of Source Code
\ngit\
- \ clone https://github.com/MASILab/PreQual.git\ncd /path/to/repo/PreQual\ngit\
- \ checkout v1.1.0\nsudo singularity build /path/to/prequal.simg Singularity\n\
+ Getting Started
\n\
+ The PreQual software is designed to run inside a Singularity container. The container requires an \"inputs\" folder that holds all required input diffusion image files (i.e.,\
+ \ .nii.gz, .bval, and .bvec files) and a configuration\
+ \ file. For those running Synb0-DisCo to correct susceptibility distortions\
+ \ without reverse phase-encoded images, this folder will also contain the structural T1 image. The container also requires an \"\
+ outputs\" folder that will hold all the outputs\
+ \ after the pipeline runs. We also need to know the image axis on which phase encoding was performed for all inputs (i.e., \"\
+ i\" for the first dimension, \"j\" for the second). To build the configuration\
+ \ file, we need to know the direction\
+ \ along said axis in which each image was phase encoded (i.e., \"+\" for positive\
+ \ direction and \"-\" for the negative direction) and the readout time for each input image. Once we have this information, we bind\
+ \ the inputs and outputs directories into the container to run the pipeline.
\nNote: The phase encoding axis, direction, and readout\
+ \ time must be known ahead of time, as this information is not stored in NIFTI\
+ \ headers. Depending on the scanner used, they may be available in JSON sidecars\
+ \ when NIFTIs are converted from DICOMs with dcm2niix.
\nContainerization\
+ \ of Source Code
\n\
+ git clone https://github.com/MASILab/PreQual.git\ncd /path/to/repo/PreQual\n\
+ git checkout v1.1.0\nsudo singularity build /path/to/prequal.simg Singularity\n\
\nWe use Singularity version 3.8 CE with root permissions.
\n\
Alternatively, a pre-built container can be downloaded here.
\nCommand
\nsingularity run \n\
- -e \n--contain\n--home /path/to/inputs/directory/\n-B /path/to/inputs/directory/:/INPUTS\n\
- -B /path/to/outputs/directory/:/OUTPUTS\n-B /tmp:/tmp\n-B /path/to/freesurfer/license.txt:/APPS/freesurfer/license.txt\n\
+ \ rel=\"nofollow\">here.\nCommand
\nsingularity run \n-e \n--contain\n\
+ --home /path/to/inputs/directory/\n-B /path/to/inputs/directory/:/INPUTS\n-B /path/to/outputs/directory/:/OUTPUTS\n\
+ -B /tmp:/tmp\n-B /path/to/freesurfer/license.txt:/APPS/freesurfer/license.txt\n\
-B /path/to/cuda:/usr/local/cuda\n--nv\n/path/to/prequal.simg\npe_axis\n[options]\n\
\n\n- Binding the freesurfer license is optional and only needed\
\ for Synb0-DisCo
\n- Binding the tmp directory is necessary when running\
@@ -36543,15 +36542,14 @@ MASILab/PreQual:
\ for matlab since it uses home for temp storage.
\n- \n
--nv\
\ and -B /path/to/cuda:/usr/local/cuda are optional. See options\
\ --eddy_cuda and --eddy_extra_args. GPU support\
- \ is currently experimental.\n \n
\nArguments and I/O
\n\n\
- - \n
Input Directory: The dtiQA_config.csv configuration\
- \ file and at least one diffusion weighted image must be provided.
\n\n\
- - \n
dtiQA_config.csv (see below for format,\
- \ must be named exactly)
\n \n- \n
<image1>.nii.gz (diffusion\
- \ weighted image)
\n \n- \n
<image1>.bval (units of s/mm2,\
- \ in the \n
\n
\nArguments and I/O
\n\n- \n
Input\
+ \ Directory: The dtiQA_config.csv configuration file and at least one\
+ \ diffusion weighted image must be provided.
\n\n- \n
dtiQA_config.csv\
+ \ (see below for format, must be named exactly)
\n\
+ \n- \n
<image1>.nii.gz (diffusion weighted image)
\n \n\
+ - \n
<image1>.bval (units of s/mm2, in the FSL format)
\n \n- \n
<image1>.bvec (normalized\
\ unit vectors in the FSL format)
\n:
\n \n- \n
<imageN>.nii.gz\
@@ -36579,49 +36577,48 @@ MASILab/PreQual:
\ The phase encoding directions of the input images along this axis are specified\
\ in the dtiQA_config.csv file. See Configuration\
\ File and Examples for more information.
\n\
- \n
\nConfiguration File
\nThe format for the lines\
- \ of the configuration CSV file, dtiQA_config.csv (must be named exactly), are\
- \ as follows:
\n<image1>,pe_dir,readout_time\n:\n<imageN>,pe_dir,readout_time\n\
-
\n\n- \n
<image> is the shared file\
- \ PREFIX between the corresponding NIFTI, BVAL, and BVEC files for that particular\
- \ image in the input directory (i.e., my_dwi.nii.gz/.bval/.bvec -> my_dwi).\
- \ Do NOT include the path to the input directory.
\n \n- \n
pe_dir\
- \ is either + or -, corresponding to the direction along the phase encoding axis\
- \ (as defined by the parameter pe_axis) on which the image is phase\
- \ encoded.
\n\n- Note that a combination of phase encoding axis and direction\
- \ map to specific anatomical (i.e. APA, APP, etc.) directions based on the orientation\
- \ of the image. So, for instance in a RAS image, an axis of j and direction of\
- \ + map to APP. We infer the orientation of the image from the header of the NIFTI\
- \ using nibabel tools and output the best anatomical phase encoding direction\
- \ interpretation of the input direction in the PDF for QA.
\n
\n \n\
- - \n
readout_time is a non-negative number, the readout_time\
- \ parameter required by FSL\u2019s eddy. The absolute value of this parameter\
- \ is used to scale the estimated b0 field. Note a value of 0 indicates that the\
- \ images are infinite bandwidth (i.e. no susceptibility distortion). See Examples for more information.
\n \n
\nExamples
\n\
- Here are some different example combinations of pe_axis, pe_dir, and readout_time\
- \ parameters and the corresponding FSL acquisition parameters lines:
\n\n\
- \n\npe_axis \npe_dir \nreadout_time \nacqparams\
- \ line \n \n\n\n\ni \n+ \n0.05 \n\
- 1, 0, 0, 0.05 \n \n\nj \n- \n0.1 \n0,\
- \ -1, 0, 0.1 \n \n\n
\nThese are examples of common\
- \ use cases. They also all share the same command, as detailed above. The PREPROCESSED\
- \ output folder will contain the final outputs and the PDF folder will contain\
- \ the QA report.
\n\n\n\nPhase Encoding
Axis \n\
- Reverse Phase
Encoded (RPE) Image \nT1
Image \nContents\
- \ of
Input Directory \nContents of
dtiQA_config.csv \n \n\
- \n\n\nj \nYes \nN/A \ndti1.nii.gz
dti1.bval
dti1.bvec
dti2.nii.gz
dti2.bval
dti2.bvec
rpe.nii.gz
rpe.bval
rpe.bvec
dtiQA_config.csv \n\
+ \n\nConfiguration File
\nThe format for the lines of the configuration\
+ \ CSV file, dtiQA_config.csv (must be named exactly), are as follows:
\n<image1>,pe_dir,readout_time\n\
+ :\n<imageN>,pe_dir,readout_time\n
\n\n- \n
<image>\
+ \ is the shared file PREFIX between the corresponding NIFTI, BVAL, and BVEC files\
+ \ for that particular image in the input directory (i.e., my_dwi.nii.gz/.bval/.bvec\
+ \ -> my_dwi). Do NOT include the path to the input directory.
\n \n\
+ - \n
pe_dir is either + or -, corresponding to the direction\
+ \ along the phase encoding axis (as defined by the parameter pe_axis)\
+ \ on which the image is phase encoded.
\n\n- Note that a combination\
+ \ of phase encoding axis and direction map to specific anatomical (i.e. APA, APP,\
+ \ etc.) directions based on the orientation of the image. So, for instance in\
+ \ a RAS image, an axis of j and direction of + map to APP. We infer the orientation\
+ \ of the image from the header of the NIFTI using nibabel tools and output the\
+ \ best anatomical phase encoding direction interpretation of the input direction\
+ \ in the PDF for QA.
\n
\n \n- \n
readout_time\
+ \ is a non-negative number, the readout_time parameter required by FSL\u2019s\
+ \ eddy. The absolute value of this parameter is used to scale the estimated b0\
+ \ field. Note a value of 0 indicates that the images are infinite bandwidth (i.e.\
+ \ no susceptibility distortion). See Examples for more\
+ \ information.
\n \n
\nExamples
\nHere are some different example combinations\
+ \ of pe_axis, pe_dir, and readout_time parameters and the corresponding FSL acquisition\
+ \ parameters lines:
\n\n\n\npe_axis \npe_dir \n\
+ readout_time \nacqparams line \n \n\n\n\n\
+ i \n+ \n0.05 \n1, 0, 0, 0.05 \n \n\nj \n\
+ - \n0.1 \n0, -1, 0, 0.1 \n \n\n
\n\
+ These are examples of common use cases. They also all share the same command,\
+ \ as detailed above. The PREPROCESSED output folder will contain the final outputs\
+ \ and the PDF folder will contain the QA report.
\n\n\n\n\
+ Phase Encoding
Axis \nReverse Phase
Encoded (RPE) Image \n\
+ T1
Image \nContents of
Input Directory \nContents of
dtiQA_config.csv \n\
+ \n\n\n\nj \nYes \nN/A \ndti1.nii.gz
dti1.bval
dti1.bvec
dti2.nii.gz
dti2.bval
dti2.bvec
rpe.nii.gz
rpe.bval
rpe.bvec
dtiQA_config.csv \n\
dti1,+,0.05
dti2,+,0.05
rpe,-,0.05 \n \n\nj \nNo \n\
Yes \ndti1.nii.gz
dti1.bval
dti1.bvec
dti2.nii.gz
dti2.bval
dti2.bvec
t1.nii.gz
dtiQA_config.csv \n\
dti1,+,0.05
dti2,+,0.05 \n \n\nj \nNo \nNo \n\
dti1.nii.gz
dti1.bval
dti1.bvec
dti2.nii.gz
dti2.bval
dti2.bvec
dtiQA_config.csv \n\
- dti1,+,0.05
dti2,+,0.05 \n \n\n
\nRunning BIDS Data
\nWhile\
+
dti1,+,0.05
dti2,+,0.05 \n \n\n
\nRunning BIDS Data
\nWhile\
\ not a BIDS pipeline, data in BIDS format can be run with PreQual without moving\
\ or copying data. The key is that the input directory structure must be as described\
\ relative to inside the container. By creatively binding files/folders\
@@ -36632,9 +36629,9 @@ MASILab/PreQual:
\nThe outputs directory and configuration file can be created\
\ wherever makes the most sense for the user. The contents of the configuration\
\ file will look something like this:
\nsub-X_ses-X_acq-1_dwi,pe_dir,readout_time\n\
- :\nsub-X_ses-X_acq-N_dwi,pe_dir,readout_time\n
\nOptions
\n--bval_threshold\
+ :\nsub-X_ses-X_acq-N_dwi,pe_dir,readout_time\n
Options
\n--bval_threshold\ \ N
\nA non-negative integer threshold under which to consider\ \ a b-value to be zero. Useful when some MRI machines do not allow for more than\ \ one b0 volume to be acquired so some users acquire scans with extremely low\ @@ -36790,12 +36787,12 @@ MASILab/PreQual: \ were acquired to label PDF output
\nDefault = subj
\n--session\ \ string
\nString describing session in which the input data were\ \ acquired to label PDF output
\nDefault = sess
\n--help,\ - \ -h
\nPipeline Assumptions
\n- \n\
-
- \n
All NIFTI images are consistent with a conversion from a DICOM using\ - \
\ndcm2niix(at least v1.0.20180622) by Chris Rorden and are raw NIFTIs without distortion\ + \ -hPipeline Assumptions
\n- \n
- \n
All NIFTI images\ + \ are consistent with a conversion from a DICOM using
dcm2niix(dcm2niixcorrectly moves the gradients from scanner\ @@ -36853,70 +36850,70 @@ MASILab/PreQual: \n - \n
No b0 drift correction is performed.
\n \n - \n
We use\ \ the fit tensor model primarily for QA. If b-values less than 500 s/mm2\ \ or greater than 1500 s/mm2 are present, we suggest careful review\ - \ of the fit prior to use for non-QA purposes.
\n \n
Pipeline Processing Steps
\n- \n
- \n
Threshold\ - \ all b-values such that values less than the
\n--bval_thresholdparameter\ - \ are 0. \n - \n
Check that all b-vectors are unit normalized and\ - \ all b-values greater than zero have associated non-zero b-vectors. For any volumes\ - \ where this is not the case, we remove them, flag a warning for the output PDF,\ - \ and continue the pipeline.
\n \n - \n
If applicable, denoise all diffusion\ - \ scans with
\ndwidenoise(Marchenko-Pastur PCA) from MrTrix3 and save\ - \ the noise profiles (needed for Rician correction later). \n - \n\
-
If applicable, perform Gibbs de-ringing on all diffusion scans with
\nmrdegibbs\ - \ from MRTrix3. \n - \n
If applicable, perform Rician correction\ - \ on all diffusion scans with the method of moments.
\n \n - \n
If applicable,\ - \ prenormalize all diffusion scans. To accomplish this, extract all b0 images\ - \ from each diffusion scan and average them. Then find a rough brain-mask with\ - \ FSL\u2019s bet and calculate an intensity scale factor such that the histogram\ - \ intersection between the intra-mask histogram of the different scans\u2019 averaged\ - \ b0s to that of the first scan is maximized. Apply this scale factor to the entire\ - \ diffusion weighted scan. This is done to avoid gain differences between different\ - \ diffusion scans.
\n- \n
- If prenormalization is not indicated, we still\ - \ run the prenormalization algorithms to calculate rough gain differences and\ - \ report the gain factors and intensity histograms in a gain QA page. The outputs\ - \ of the algorithms, however, are NOT propagated through to the rest of the pipeline. \n\ -
\n - \n
Prepare data for and run preprocessing with topup and eddy
\n\ -- \n
- \n
Topup:
\n- \n
- \n
Extract all b0s from all scans, maintaining\ - \ their relative order.
\n \n - \n
(Optional) If a T1 is supplied and\ - \ no complementary (i.e. reverse) phase encoded images are provided, use Synb0-DisCo\ - \ to convert the first b0 of the first scan to a susceptibility-corrected b0.
\n\ - \n - \n
Build the acquisition parameters file required by both topup and\ - \ eddy
\n- \n
- \n
For the number of b0s from each image, add the same\ - \ phase encoding and readout time line to the acquisition parameters file, as\ - \ outlined in \"Example Phase Encoding Schemes\".
\n- \n
- Example: In the\ + \ of the fit prior to use for non-QA purposes.\n \n
- \n
- \n
- \n
- \n
Pipeline Processing\ + \ Steps
\n\ +- \n
- \n
Threshold all b-values such that values less than the
\n--bval_threshold\ + \ parameter are 0. \n - \n
Check that all b-vectors are unit normalized\ + \ and all b-values greater than zero have associated non-zero b-vectors. For any\ + \ volumes where this is not the case, we remove them, flag a warning for the output\ + \ PDF, and continue the pipeline.
\n \n - \n
If applicable, denoise\ + \ all diffusion scans with
\n\ +dwidenoise(Marchenko-Pastur PCA) from\ + \ MrTrix3 and save the noise profiles (needed for Rician correction later). \n - \n
If applicable, perform Gibbs de-ringing on all diffusion scans\ + \ with
\nmrdegibbsfrom MRTrix3. \n - \n
If applicable,\ + \ perform Rician correction on all diffusion scans with the method of moments.
\n\ + \n - \n
If applicable, prenormalize all diffusion scans. To accomplish\ + \ this, extract all b0 images from each diffusion scan and average them. Then\ + \ find a rough brain-mask with FSL\u2019s bet and calculate an intensity scale\ + \ factor such that the histogram intersection between the intra-mask histogram\ + \ of the different scans\u2019 averaged b0s to that of the first scan is maximized.\ + \ Apply this scale factor to the entire diffusion weighted scan. This is done\ + \ to avoid gain differences between different diffusion scans.
\n- \n
- If\ + \ prenormalization is not indicated, we still run the prenormalization algorithms\ + \ to calculate rough gain differences and report the gain factors and intensity\ + \ histograms in a gain QA page. The outputs of the algorithms, however, are NOT\ + \ propagated through to the rest of the pipeline. \n
\n - \n
Prepare\ + \ data for and run preprocessing with topup and eddy
\n- \n
- \n
Topup:
\n\ +- \n
- \n
Extract all b0s from all scans, maintaining their relative order.
\n\ + \n - \n
(Optional) If a T1 is supplied and no complementary (i.e. reverse)\ + \ phase encoded images are provided, use Synb0-DisCo to convert the first b0 of\ + \ the first scan to a susceptibility-corrected b0.
\n \n - \n
Build\ + \ the acquisition parameters file required by both topup and eddy
\n- \n\
+
- \n
For the number of b0s from each image, add the same phase encoding and\ + \ readout time line to the acquisition parameters file, as outlined in \"Example\ + \ Phase Encoding Schemes\".
\n- \n
- Example: In the case where we have\ + \ a phase encoding axis of j and two images, one with 7 b0s, + direction, and\ + \ 0.05 readout time and one with 3 b0s, - direction, and 0.02 readout time, this\ + \ file will have 10 lines. The first 7 lines are identical and equal to [0, 1,\ + \ 0, 0.05]. The last three lines are also identical and equal to [0, -1, 0, 0.02]. \n\ +
\n - \n
(Optional) If Synb0-DisCo is run because no complementary\ + \ phase encoding directions are supplied and --synb0 is not off, we add an additional\ + \ line to the end of the file. This line is the same as the first line of the\ + \ file except that the readout time is 0 instead.
\n- \n
- Example: In the\ \ case where we have a phase encoding axis of j and two images, one with 7 b0s,\ - \ + direction, and 0.05 readout time and one with 3 b0s, - direction, and 0.02\ - \ readout time, this file will have 10 lines. The first 7 lines are identical\ - \ and equal to [0, 1, 0, 0.05]. The last three lines are also identical and equal\ - \ to [0, -1, 0, 0.02]. \n
\n - \n
(Optional) If Synb0-DisCo\ - \ is run because no complementary phase encoding directions are supplied and --synb0\ - \ is not off, we add an additional line to the end of the file. This line is the\ - \ same as the first line of the file except that the readout time is 0 instead.
\n\ -- \n
- Example: In the case where we have a phase encoding axis of j and two\ - \ images, one with 7 b0s, + direction, and 0.05 readout time and one with 3 b0s,\ - \ + direction, and 0.02 readout time, this file will have 11 lines. The first\ - \ 7 lines are identical and equal to [0, 1, 0, 0.05]. The next three lines are\ - \ also identical and equal to [0, 1, 0, 0.02]. Finally, the last line is equal\ - \ to [0, 1, 0, 0]. \n
\n
\n - \n
- \n
We then concatenate\ - \ all the b0s maintaining their order and run topup with the acquisition parameters\ - \ file if images with complementary phase encoding directions are supplied or\ - \ if a T1 was supplied. Otherwise, we move on to the next step, eddy.
\n \n\
-
\n - \n
- \n
Eddy
\n- \n
- \n
Using the acquisition parameters\ - \ file from the topup step, regardless of whether topup was performed, we build\ - \ the eddy index file such that each volume in each image corresponds to the line\ - \ in the acquisition parameters file associated with the first b0 of each scan.\ - \ This is done to tell eddy that each volume in a given scan has the same underlying\ - \ phase encoding scheme as the first b0 of that scan.
\n- \n
- Example:\ - \ In the case where we have two images, one with 7 b0s and 100 total volumes and\ - \ one with 3 b0s and 10 total volumes, the eddy index file has 100 1\u2019s followed\ - \ by 10 8\u2019s. \n
\n - \n
Eddy is then run with either a\ - \ mask generated with bet and the -f 0.25 and -R options or without a mask (aka\ - \ with a mask of all 1\u2019s), depending on user input (see the --eddy_mask option)\ - \ and with the output of topup if topup was run. Eddy also runs with the --repol\ - \ option for outlier slice replacement. We also first run eddy with a check looking\ - \ for shelled data. If the check fails, eddy is then run with the --data_is_shelled\ + \ + direction, and 0.05 readout time and one with 3 b0s, + direction, and 0.02\ + \ readout time, this file will have 11 lines. The first 7 lines are identical\ + \ and equal to [0, 1, 0, 0.05]. The next three lines are also identical and equal\ + \ to [0, 1, 0, 0.02]. Finally, the last line is equal to [0, 1, 0, 0].
\n\
+
\n - \n
\n - \n
- \n
We then concatenate all the b0s maintaining\ + \ their order and run topup with the acquisition parameters file if images with\ + \ complementary phase encoding directions are supplied or if a T1 was supplied.\ + \ Otherwise, we move on to the next step, eddy.
\n \n
Eddy
\n- \n
- \n
Using the acquisition parameters file from the topup\ + \ step, regardless of whether topup was performed, we build the eddy index file\ + \ such that each volume in each image corresponds to the line in the acquisition\ + \ parameters file associated with the first b0 of each scan. This is done to tell\ + \ eddy that each volume in a given scan has the same underlying phase encoding\ + \ scheme as the first b0 of that scan.
\n- \n
- Example: In the case where\ + \ we have two images, one with 7 b0s and 100 total volumes and one with 3 b0s\ + \ and 10 total volumes, the eddy index file has 100 1\u2019s followed by 10 8\u2019\ + s. \n
\n - \n
Eddy is then run with either a mask generated\ + \ with bet and the -f 0.25 and -R options or without a mask (aka with a mask of\ + \ all 1\u2019s), depending on user input (see the --eddy_mask option) and with\ + \ the output of topup if topup was run. Eddy also runs with the --repol option\ + \ for outlier slice replacement. We also first run eddy with a check looking for\ + \ shelled data. If the check fails, eddy is then run with the --data_is_shelled\ \ flag to force eddy to run on all scans, DSI included. Note that DSI data is\ \ not officially supported by FSL\u2026 yet?
\n- \n
- \n
If eddy detects\ \ data is not shelled, we report this as a warning
\n \n - \n
As noted\ @@ -36948,16 +36945,16 @@ MASILab/PreQual: \ analysis later. dwi2tensor does this for us.
\n
\n - \n
- \n
We\ \ then convert the tensor to FA and MD images (and visualize them later too) as\ \ well as AD, RD, and V1 eigenvector images for the user. The latter 3 are not\ - \ visualized.
\n \n
Pipeline\ - \ Quality Assurance Steps
\n- \n
- \n
We start with the brain mask generated\ - \ above to generate a mask used for the following quantification of tensor fit\ - \ using a chi-squared statistic.
\n- \n
- \n
First, we calculate the mean\ - \ image for each unique b-value (0 not included). Then we run FSL\u2019s FAST\ - \ to isolate the CSF on each meaned image. We then take the average probability\ - \ of a voxel being CSF across all unique b-values and assign >15% probability\ - \ to be a positive CSF voxel.
\n \n - \n
Then we call the final chi-squared\ + \ visualized.
\n \n
Pipeline\ + \ Quality Assurance Steps
\n- \n
- \n
We start with the brain mask generated above\ + \ to generate a mask used for the following quantification of tensor fit using\ + \ a chi-squared statistic.
\n- \n
- \n
First, we calculate the mean image\ + \ for each unique b-value (0 not included). Then we run FSL\u2019s FAST to isolate\ + \ the CSF on each meaned image. We then take the average probability of a voxel\ + \ being CSF across all unique b-values and assign >15% probability to be a\ + \ positive CSF voxel.
\n \n - \n
Then we call the final chi-squared\ \ mask to be the intersection of the inverted CSF mask and a 1-pixel eroded version\ \ of the brain mask.
\n \n
\n - \n
- \n
On the voxels inside the\ \ chi-squared mask, we perform the following quality assurance:
\n- \n
- \n\ @@ -37020,15 +37017,15 @@ MASILab/PreQual: \ FA map clipped from 0 to 1 as well as the average FA for the Hopkins ROIs and\ \ the quality of the atlas registration.\n \n
- \n
Lastly, we visualize\ \ some central slices of the MD map clipped from 0 to 0.003 (ADC of water at 37\xB0\ - C).
\n \n
\n
Outputs
\n<imageN_%> denotes the\ - \ original prefix of imageN with the preceding preprocessing step descriptors\ - \ tacked on the end. For example, in the case of the PRENORMALIZED directory,\ - \ the prefix for imageJ may or may not include \"_denoised\" depending on whether\ - \ the denoising step was run.
\nFolders and files in bold\ - \ are always included.
\nFolders and files in italics are removed\ - \ if
\n--keep_intermediatesis NOT indicated- \n
- \n
THRESHOLDED_BVALS
\n\ + C).\n \n
\n - \n
Outputs
\n<imageN_%> denotes the original prefix\ + \ of imageN with the preceding preprocessing step descriptors tacked on the end.\ + \ For example, in the case of the PRENORMALIZED directory, the prefix for imageJ\ + \ may or may not include \"_denoised\" depending on whether the denoising step\ + \ was run.
\nFolders and files in bold are always included.
\n\ +Folders and files in italics are removed if --keep_intermediates\
+ \ is NOT indicated
- \n
- \n
THRESHOLDED_BVALS
\n\- \n
- \n
<image1>.bval
\n:
\n \n - \n\
<imageN>.bval
\n \n
\n - \n
- \n
CHECKED\ \ (these contain the volumes that have passed the bval/bvec checks)
\n- \n\
@@ -37126,13 +37123,13 @@ MASILab/PreQual:
\ per
- \n
dwmri.bval
\n \n - \n
dwmri.bvec
\n\ \n
dwigradcheckand are only used for QA purposes)\n- \n\
\n - \n
- \n
PDF
\n- \n
- \ndtiQA.pdf\ - \ (final QA document) \n
\n
Note on\ - \ Versioning for VUIIS XNAT Users
\nPreQual was developed at Vanderbilt\ - \ under the project name \"dtiQA v7 Multi\". PreQual v1.0.0 represents dtiQA v7.2.0.\ + \ (final QA document)
Note\ + \ on Versioning for VUIIS XNAT Users
\nPreQual was developed at Vanderbilt under\ + \ the project name \"dtiQA v7 Multi\". PreQual v1.0.0 represents dtiQA v7.2.0.\ \ Thus, on XNAT, dtiQA v7.2.x refers to PreQual v1.0.x.
\n" - stargazers_count: 26 + stargazers_count: 33 subscribers_count: 1 topics: - diffusion @@ -37140,7 +37137,7 @@ MASILab/PreQual: - preprocessing - quality - assurance - updated_at: 1681220660.0 + updated_at: 1696841326.0 MASILab/Synb0-DISCO: data_format: 2 description: Distortion correction of diffusion weighted MRI without reverse phase-encoding @@ -38114,22 +38111,22 @@ MPIB/singularity-fsl: data_format: 2 description: various singularity recipes for FSL filenames: - - Singularity.6.0.6.1 - Singularity.6.0.2-Cuda8-xtract_viewer - - Singularity.5.0.11 - - Singularity.6.0.5 - - Singularity.6.0.2-Cuda8 - - Singularity.6.0.6 - - Singularity.6.0.1 - - Singularity.6.0.3 - - Singularity.5.0.10 - - Singularity.6.0.0 + - Singularity.5.0.9 - Singularity.6.0.2 - - Singularity.6.0.4-Cuda8 - Singularity.6.0.5.1 - Singularity.6.0.4 - - Singularity.5.0.9 + - Singularity.6.0.6 + - Singularity.6.0.4-Cuda8 + - Singularity.5.0.10 + - Singularity.5.0.11 + - Singularity.6.0.0 + - Singularity.6.0.6.1 + - Singularity.6.0.3 - Singularity.5-Cuda8 + - Singularity.6.0.1 + - Singularity.6.0.2-Cuda8 + - Singularity.6.0.5 full_name: MPIB/singularity-fsl latest_release: null readme: '![\"Build](\"https://travis-ci.org/Molmed/checkQC.svg?branch=master\"\)
![](\"assert/figures/seg.png\"\)
\n![](\"assert/figures/pose.png\"\)
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![\"Current](\"https://img.shields.io/github/v/release/divonlan/genozip\"\ "\\"Current")
![\"Issues\"](\"https://img.shields.io/github/issues/josephwkania/radio_transients?style=flat-square\"\)
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