**Establishing a reproducible and sustainable analysis workflow** ##
**Clare Kelly, Mélanie Garcia**, Trinity College Dublin
**Relevant work:** Mélanie's code on GitHub is [here][1]
**Softwares/programs requirements:** Python notebook (see the [first presentation][2]), Git (see installation instructions [here][3]), [GitHub][4]
**AOMICS dataset:** [PIOP2][5]
**Modalities:** T1w, fMRI
**Abstract:**
This tutorial will describe how to use Python notebooks to write reproducible code. We will demonstrate best practice for pipeline/code management and versioning using Git. We will end by recommending approaches for sustainable analyses: optimising work practices and code to reduce resource use. Here, we reference work by the OHBA Sustainability special interest group (https://neuropipelines.github.io/index). This session will be copresented by Mélanie Garcia,
[1]: https://github.com/garciaml/my-analysis
[2]: https://osf.io/teqxb/
[3]: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git
[4]: https://github.com/
[5]: https://openneuro.org/datasets/ds002790