https://peertube.watch/videos/watch/11619728-abbd-4a67-8a3e-e12e83dfa3d9 Diagnosing genetic diseases presents significant challenges. Modern sequencers produce vast amounts of data, requiring intensive processing and filtering before analysis. The intricate mechanisms in rare diseases necessitate a high level of expertise from biologists to identify potential causes. This is why it is crucial to demonstrate these results come from accurate, efficient, and reproducible bioinformatics pipelines. Indeed, accuracy is vital for patient diagnosis, efficiency is needed to handle the growing data volume and patient backlog, and reproducibility is essential to ensure the quality of the results. This talk is aimed at a diverse audience and will give feedback on Nix integration in our workflow. It will focus on how Nix significantly improved reproducibility and discuss some challenges we encountered, especially with large databases and running on high-performance computing architectures. Speaker: Alexis Praga, Track: Nix and NixOS devroom, Room: H.1302 (Depage), When: Sunday 4 February 2024, 11:00–11:05 (Brussels time), Schedule: FOSDEM 2024 event page, Slides & links Slides in PDF, Slides online, Licence: Creative Commons Attribution 2.0 Belgium (CC BY 2.0 BE) (as stated in the FOSDEM video archive). Attribution: “Nix for genetics : powering a bioinformatics pipeline” by Alexis Praga, FOSDEM 2024. Original recording: 2024/h1302/fosdem-2024-3058-nix-for-genetics-powering-a-bioinformatics-pipeline.av1.webm from the FOSDEM video archive. This channel is an unofficial mirror; FOSDEM is a free and non-commercial event organised by the community for the community. Mon, 26 Oct 2026 02:08:05 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://peertube.watch https://peertube.watch/lazy-static/avatars/3b284627-b75f-409e-ac2e-10f4c2946f43.png https://peertube.watch/videos/watch/11619728-abbd-4a67-8a3e-e12e83dfa3d9 All rights reserved, unless otherwise specified in the terms specified at https://peertube.watch/about and potential licenses granted by each content's rightholder.