AUTHOR: [email protected]
A fairly compact and efficient processing pipeline implemented in Bash and Python using afni_proc.py and the batch processing system SLURM on Biowulf the HPC cluster at the NIH.
Examples: see
h_15xx_proc.sh
$> hDsAp5_swob_v5a?.sh -h
$> cd output/directory
$> hDsAp5_swob_v5a?.sh -t sleep -S All /input/data/dir
hDsAp5_swob_*
will copy the folder structure and links to the sub-*_task-sleep_*.nii
files found in /input/data/dir
. It will also create run_swarm.sh
and swarm_jobs.sh
in the output dir.
run_swarm
submits the jobs in swarm_jobs.sh
to SLURM. Each compute node executes hDsAp5_swob_v5a?.sh -J All
on one experiment in one of the output directories. The parameter All
selects a subset of parameters for afni_proc.py
. See also hDsAp5_swob_v5a?.sh -h
.
-
Log files:
.../output/directory/log/slurm-*.out
-
A great number of AFNI output files are found in:
../out/dir/sub-00001/ses-1/run-$ExId/$ExId.results/
- View quality-control output in
../$ExId.results/QC*/index.html
Epi_Mc.nii
Preprocessed fMRI time series, aligned to Talairach space by default.McPar.1D
(=dfile*.1D
) : time*6 motion parametersAnaT1_1mm.nii
: T1W anatomy, aligned to Talairach by non-lin. warp
- View quality-control output in