A Python tool for launching neuroimaging analysis pipelines on HPC clusters with reproducible, BIDS-compliant workflows.
Developed at BCBL – Basque Center on Cognition, Brain and Language.
launchcontainers manages three phases of a neuroimaging analysis:
lc prepare → lc run → lc qc
prepare validates inputs, freezes your configs into the analysis directory,
and generates per-subject HPC launch scripts.
run submits those scripts to SLURM, SGE, or runs them locally.
qc checks outputs and writes a failed_subseslist.tsv for easy re-submission.
| Type | Pipelines |
|---|---|
| DWI / structural (container-based) | anatrois, freesurferator, rtppreproc, rtp-pipeline, rtp2-preproc, rtp2-pipeline |
| fMRI (analysis-based) | glm, prf |
# 1. Install pipx and poetry (once per machine)
pip install pipx
pipx install poetry
# 2. Clone and set up the virtual environment
git clone https://github.com/your-org/launchcontainers.git
cd launchcontainers
poetry env use python3
poetry install
# 3. Activate the environment
poetry shelllc copy_configs --output /path/to/basedir/code/
# edit lc_config.yaml and subseslist.tsv
lc prepare --lc_config lc_config.yaml --sub_ses_list subseslist.tsv --container_specific_config rtppreproc.json
lc run --workdir /path/to/analysis-dir --run_lc
lc qc --workdir /path/to/analysis-dirFull documentation — config reference, CLI reference, step-by-step tutorial,
and the developer extension guide — lives in docs/.
Build locally:
pip install sphinx sphinx-rtd-theme
cd docs && make html
open build/html/index.htmlMIT — see LICENSE.
Copyright © 2020–2026 Garikoitz Lerma-Usabiaga Copyright © 2020–2022 Mengxing Liu Copyright © 2022–2023 Leandro Lecca Copyright © 2022–2026 Yongning Lei Copyright © 2023 David Linhardt Copyright © 2023 Iñigo Tellaetxe