{"name":"napari-racc","display_name":"RACC","visibility":"public","icon":"","categories":[],"schema_version":"0.2.1","on_activate":null,"on_deactivate":null,"contributions":{"commands":[{"id":"napari-racc.make_widget","title":"RACC","python_name":"napari_racc._widget:RaccWidget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-racc.sample_data_2d","title":"RACC example 2D","python_name":"napari_racc._sample_data:make_sample_data_2d","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-racc.sample_data_3d","title":"RACC example 3D","python_name":"napari_racc._sample_data:make_sample_data_3d","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":null,"writers":null,"widgets":[{"command":"napari-racc.make_widget","display_name":"RACC","autogenerate":false}],"sample_data":[{"command":"napari-racc.sample_data_2d","key":"racc_2d","display_name":"RACC 2D example"},{"command":"napari-racc.sample_data_3d","key":"racc_3d","display_name":"RACC 3D example"}],"themes":null,"menus":{},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.4","name":"napari-racc","version":"0.1.0","dynamic":["license-file"],"platform":null,"supported_platform":null,"summary":"Regression adjusted colocalisation colour mapping for napari","description":"# napari-racc\n\n`napari-racc` is a napari plugin for Regression Adjusted Colocalisation Colour\nMapping (RACC), a qualitative visualization method for 2D and 3D fluorescence\nmicroscopy data.\n\nThe plugin takes two image layers, computes the RACC index in 3D whenever the\ninputs are volumes, and adds interactive overlay, RACC, side-by-side, MIP, and\nscatter-plot views to the napari viewer.\n\n## Features\n\n- two-channel RACC calculation from napari `Image` layers\n- live threshold, theta, percentile, and Costes threshold controls\n- transparent zero-valued RACC voxels for clean volume rendering\n- thresholded RGB overlay volume with selectable probe colors\n- side-by-side overlay/RACC and 3D-derived MIP views\n- scatter histogram with regression, threshold, and percentile-band overlays\n- XY and Z display scale controls for metadata-light TIFF stacks\n\n## Installation\n\nInstall from PyPI once the package has been published:\n\n```bash\npip install napari-racc\n```\n\nFor local development:\n\n```bash\ngit clone https://github.com/rensutheart/napari-racc.git\ncd napari-racc\nuv venv --python 3.11\nsource .venv/bin/activate\nuv pip install -e \".[dev]\"\n```\n\nFish shell users should activate the environment with:\n\n```fish\nsource .venv/bin/activate.fish\n```\n\n## Usage\n\n1. Open napari.\n2. Open two image stacks or use `File > Open Sample > RACC`.\n3. Start the widget from `Plugins > RACC > RACC`.\n4. Select channel 1 and channel 2.\n5. Adjust thresholds manually or press `Costes thresholds`.\n6. Press `Run RACC`.\n7. Use `Overlay`, `RACC`, `Side by side`, and `MIPs` to switch views.\n\nRACC is calculated over the full 3D volume when 3D inputs are used. The MIP view\nis derived from the 3D calculation; it is not a 2D recalculation.\n\n## Development\n\n```bash\npython -m npe2 validate src/napari_racc/napari.yaml\npython -m ruff check src\npython -m pytest\npython -m build\n```\n\nLaunch one example dimensionality at a time:\n\n```bash\npython scripts/launch_racc_examples.py --example 3d\npython scripts/launch_racc_examples.py --example 2d\n```\n\nDo not launch the napari viewer with `QT_QPA_PLATFORM=offscreen`; napari needs a\nreal Qt/OpenGL context for the viewer on macOS.\n\n## Citation\n\nIf you use this plugin or the RACC method in research, cite:\n\nTheart RP, Loos B, Niesler TR. Regression adjusted colocalisation colour mapping\n(RACC): A novel biological visual analysis method for qualitative\ncolocalisation analysis of 3D fluorescence micrographs. PLOS ONE 14(11):\ne0225141. <https://doi.org/10.1371/journal.pone.0225141>\n\n## License And Patent Notice\n\nThis software is licensed under the PolyForm Noncommercial License 1.0.0. It is\nsource-available for noncommercial research, education, and evaluation use, but\nit is not an OSI open-source license.\n\nUse of the RACC method may be covered by patent rights, including US patent\napplication US20220189129A1 and related patent family members. Commercial,\nclinical, diagnostic, or for-profit service use requires a separate license from\nthe rights holder. See `LICENSE`, `NOTICE`, and `PATENTS.md`.\n","description_content_type":"text/markdown","keywords":"colocalisation,colocalization,fluorescence microscopy,image analysis,napari,RACC,visualization","home_page":null,"download_url":null,"author":"Rensu P. Theart","author_email":null,"maintainer":null,"maintainer_email":null,"license":null,"classifier":["Framework :: napari","Intended Audience :: Science/Research","Programming Language :: Python :: 3","Programming Language :: Python :: 3 :: Only","Topic :: Scientific/Engineering :: Bio-Informatics","Topic :: Scientific/Engineering :: Image Processing","Topic :: Scientific/Engineering :: Visualization"],"requires_dist":["imageio>=2.20","magicgui>=0.7","numpy>=1.24","qtpy>=2.4","tifffile>=2022.7.28","build>=1.2; extra == \"dev\"","napari[pyqt6]>=0.6; extra == \"dev\"","npe2>=0.8; extra == \"dev\"","pytest>=8; extra == \"dev\"","pytest-qt>=4.4; extra == \"dev\"","ruff>=0.12; extra == \"dev\"","twine>=5; extra == \"dev\""],"requires_python":">=3.10","requires_external":null,"project_url":["Homepage, https://github.com/rensutheart/napari-racc","Repository, https://github.com/rensutheart/napari-racc","Issues, https://github.com/rensutheart/napari-racc/issues","Paper, https://doi.org/10.1371/journal.pone.0225141","Patent, https://patentimages.storage.googleapis.com/f1/10/5d/798b2ae1eea441/US20220189129A1.pdf"],"provides_extra":["dev"],"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}