TY - JOUR TI - Tapenade: Spatial Quantification of Mechanical and Genetic Fields in Dense 3D Organoids From Cell to Tissue Scale AU - Gros, Alice AU - Vanaret, Jules AU - Tlili, Sham AU - Guignard, Léo VL - 16 IS - 19 PY - 2026 DA - 2026/10/05 SP - e5823 C1 - Bio-protocol 2026;16:e5823 DO - 10.21769/BioProtoc.5823 UR - https://doi.org/10.21769/BioProtoc.5823 AB - Whole-mount 3D imaging of multilayered biological tissues enables quantitative analysis of cell states and organization in their spatial context. However, extracting unbiased and meaningful quantitative information from dense, multilayered samples remains challenging due to imaging artifacts, increased density, and limited signal-to-noise ratio. Open source bioimage analysis workflows tailored to this type of analysis are scarce, and analysis bottlenecks like image curation or cell segmentation are seldom available without coding expertise. Here, we present a step-by-step computational protocol for the analysis of dense 3D organoid datasets using the Tapenade (Thorough Analysis PipEliNe for Advanced DEep imaging) workflow. Starting from multichannel image stacks, the protocol guides users through software installation, registration and fusion of multi-view datasets, preprocessing, and nuclei segmentation. It further details the generation of quantitative outputs, including morphometric measurements, deformation fields, and spatial correlation analyses. The workflow can be executed through open-source Python scripts or user-friendly Napari interfaces, allowing interactive parameter tuning and 3D visualization at each stage. This pipeline provides an accessible and modular framework for nonspecialist users to perform reproducible, multiscale quantitative analysis of 3D organoid images, while retaining flexibility for advanced users to customize individual steps. KW - 3D image analysis KW - Organoids KW - Nuclei segmentation KW - Quantitative analysis KW - Spatial correlation KW - Multiscale KW - Open-source JF - Bio-protocol SN - 2331-8325 PB - Bio-protocol LLC. BIO101 - False