This is a prototype AFNI bids app implmenting participant level preprocessing with afni_proc.py. This pipeline is currently doing temporal alignment, nonlinear registration to standard space, bluring of 4 mm, masking, and scaling for all epis in the input bids dataset using the following afni proc command:
afni_proc.py -subj_id {subj_id} \
-script proc.bids -scr_overwrite -out_dir {out_dir} \
-blocks tshift align tlrc volreg blur mask scale \
-copy_anat {anat_path} -tcat_remove_first_trs 0 \
-dsets {epi_paths} -align_opts_aea -cost lpc+ZZ -giant_move \
-tlrc_base MNI152_T1_2009c+tlrc -tlrc_NL_warp \
-volreg_align_to MIN_OUTLIER \
-volreg_align_e2a -volreg_tlrc_warp -blur_size 4.0 -bash"""Documenation for afni_proc.py is available here.
Specific issues with this BIDS App should be reported on its issues page. AFNI issues should be posted to the AFNI Message Board
Please cite the 1996 paper if you use AFNI: Cox RW (1996) AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 29(3):162–173
This App has the following command line arguments:
usage: run.py [-h]
[--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
bids_dir output_dir
Example BIDS App entry point script.
positional arguments:
bids_dir The directory with the input dataset formatted
according to the BIDS standard.
output_dir The directory where the output files should be stored.
If you are running a group level analysis, this folder
should be prepopulated with the results of
the participant level analysis.
{participant} Level of the analysis that will be performed. Multiple
participant level analyses can be run independently
(in parallel). Only "participant" is currently supported.
optional arguments:
-h, --help show this help message and exit
--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]
The label(s) of the participant(s) that should be
analyzed. The label corresponds to
sub-<participant_label> from the BIDS spec (so it does
not include "sub-"). If this parameter is not provided
all subjects will be analyzed. Multiple participants
can be specified with a space separated list.
--afni_proc AFNI_PROC
Optional: command string for afni proc. Parameters
that vary by subject should be encapsulated in curly
braces and must all be included {{subj_id}},
{{out_dir}}, {{anat_path}}, or {{epi_paths}}.The first
_T1w for each subject will currently be used as the
anat.All of the _bold will be used as the
functionals.Example:-subj_id {subj_id} -script
proc.bids -scr_overwrite -out_dir {{out_dir}} -blocks
tshift align tlrc volreg blur mask scale -copy_anat
{{anat_path}} -tcat_remove_first_trs 0 -dsets
{{epi_paths}} -align_opts_aea -cost lpc+ZZ -giant_move
-tlrc_base MNI152_T1_2009c+tlrc -tlrc_NL_warp
-volreg_align_to MIN_OUTLIER
-volreg_align_e2a -volreg_tlrc_warp -blur_size 4.0 -bash"""To run it in participant level mode (for one participant):
docker run -i --rm \
-v /Users/filo/data/ds005:/bids_dataset:ro \
-v /Users/filo/outputs:/outputs \
bids/example \
/bids_dataset /outputs participant --participant_label 01This is a very early prototype. More functionality is likely coming. Expect breaking changes.