**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