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manifest.json
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{
"author": "Intermountain Neuroimaging Consortium",
"cite": "https://tedana.readthedocs.io/en/stable/",
"command": "python /flywheel/v0/run.py",
"config": {
"echo-times": {
"optional": true,
"description": "Space seperated list of echo times TE: e1 e2 e3.",
"type": "string"
},
"output-layout": {
"default": "legacy",
"description": "Organization of outputs (bids|legacy)",
"type": "string",
"enum": [
"bids",
"legacy"
]
},
"explicit-mask": {
"type":"boolean",
"default": false,
"description": "Use explicit mask computed during fmriprep for analysis."
},
"command-line-args": {
"optional": true,
"description": "additional command line arguments outlined in tedana's usage notes",
"type": "string"
},
"gear-log-level": {
"default": "INFO",
"description": "Gear Log verbosity level (ERROR|WARNING|INFO|DEBUG)",
"type": "string",
"enum": [
"ERROR",
"WARNING",
"INFO",
"DEBUG"
]
},
"gear-dry-run": {
"default": false,
"description": "pretend command ran",
"type": "boolean"
},
"gear-writable-dir": {
"default": "/pl/active/ics/fw_temp_data",
"description": "Gears expect to be able to write temporary files in /flywheel/v0/. If this location is not writable (such as when running in Singularity), this path will be used instead. fMRIPrep creates a large number of files so this disk space should be fast and local.",
"type": "string"
},
"slurm-cpu": {
"default": "1",
"description": "[SLURM] How many cpu-cores to request per command/task. This is used for the underlying '--cpus-per-task' option. If not running on HPC, then this flag is ignored",
"type": "string"
},
"slurm-ram": {
"default": "12G",
"description": "[SLURM] How much RAM to request. This is used for the underlying '--mem-per-cpu' option. If not running on HPC, then this flag is ignored",
"type": "string"
},
"slurm-ntasks": {
"default": "1",
"description": "[SLURM] Total number of tasks/commands across all nodes (not equivalent to neuroimaging tasks). Using a value greater than 1 for code that has not been parallelized will not improve performance (and may break things).",
"type": "string"
},
"slurm-nodes": {
"default": "1",
"description": "[SLURM] How many HPC nodes to run on",
"type": "string"
},
"slurm-partition": {
"default": "blanca-ics",
"description": "[SLURM] Blanca, Alpine, or Summit partitions can be entered",
"type": "string"
},
"slurm-qos": {
"default": "blanca-ics",
"description": "[SLURM] For Blanca the QOS has a different meaning, ie blanca-ics vs blanca-ibg, etc. For Alpine and Summit, the QOS should be set to normal if running a job for 1 day or less, and set to long if running a job with a maximum walltime of 7 days",
"type": "string"
},
"slurm-account": {
"default": "blanca-ics",
"description": "[SLURM] For Blanca the ACCOUNT should be set to the sub-account of choice (e.g. blanca-ics-rray). For Alpine, the account should be set to ucb-general, or the specialized account granted by RC: ucb278_asc1",
"type": "string"
},
"slurm-time": {
"default": "1428",
"description": "[SLURM] Maximum walltime requested after which your job will be cancelled if it hasn't finished. Default to 1 day",
"type": "string"
}
},
"custom": {
"flywheel": {
"classification": [
"fMRI"
],
"components": [
"python"
],
"modality": [
"MR"
],
"suite": "Denoising",
"type": [
"NIFTI"
]
},
"gear-builder": {
"category": "analysis",
"image": "amhe4269/fw-tedana:23.0.1_inc0.5"
},
"license": "Apache-2.0"
},
"description": "(HPC Compatible) TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI) data. Tedana should be used for optimal weighting methods and denoising preprocessed multi-echo fmri data.",
"environment": {
"USER": "flywheel",
"PATH": "/opt/poetry/bin:/opt/venv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
"REQUESTS_CA_BUNDLE": "/etc/ssl/certs/ca-certificates.crt",
"python3": "/opt/venv/bin/python3",
"python": "/opt/venv/bin/python",
"FLYWHEEL": "/flywheel/v0",
"POETRY_HOME": "/opt/poetry",
"POETRY_VERSION": "1.1.13",
"POETRY_VIRTUALENVS_CREATE": "false"
},
"inputs": {
"api-key": {
"base": "api-key"
},
"fmriprep_zip": {
"description": "(Optional) Pass entire preprocessed session level dataset from fmriprep preprocessing. Tedana will be run on all fmri ME acquisitions.",
"base": "file",
"optional": true
},
"fmri_echo_1": {
"description": "(Optional) Alternative method to pass preprocessed fmri multi echo separately (one echo per input).",
"base": "file",
"optional": true
},
"fmri_echo_2": {
"description": "(Optional) Alternative method to pass preprocessed fmri multi echo separately (one echo per input).",
"base": "file",
"optional": true
},
"fmri_echo_3": {
"base": "file",
"description": "(Optional) Alternative method to pass preprocessed fmri multi echo separately (one echo per input).",
"optional": true
}
},
"label": "Tedana: TE dependent analysis",
"license": "MIT",
"maintainer": "Amy Hegarty <[email protected]>",
"name": "fw-tedana",
"source": "https://github.com/intermountainneuroimaging/fw-tedana",
"url": "https://tedana.readthedocs.io/en/stable/index.html",
"version": "23.0.1_inc0.5"
}