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7 results for “ome-zarr”
OME-Zarr 3D hiPSCs with 3D labels & 3D measurements, 2x2 field of views
<p>These are 2 small OME-Zarr files of the data from <a href="../records/7057076">10.5281/zenodo.7057076</a>.</p> <p>The images have been processed using <a href="https://fractal-analytics-platform.github.io/">Fractal</a>, the workflow is attached as a json file. It ran with fractal-server==2.3.6, fractal-client==2.0.1, fractal-web==1.4.0 and fractal-tasks-core==1.2.1.</p> <p>Both Zarr files are Zip-compressed to allow easier upload & download from Zenodo. </p> <p>20200812-CardiomyocyteDifferentiation14-Cycle1.zarr contains 3 3D channels, a nuclear segmentation produced by <a href="https://cellpose.readthedocs.io/en/latest/">cellpose</a> as labels and 4 tables: A ROI table for the whole well, a ROI table for the 4 field of views, a masking ROI table for the nuclear segmentation, as well as measurements performed with <a href="https://github.com/haesleinhuepf/napari-skimage-regionprops">napari-skimage-regionprops</a>.</p> <p>20200812-CardiomyocyteDifferentiation14-Cycle1_mip.zarr contains the same 3 channels, but as maximum intensity projections. It contains nuclear segmentation through cellpose, as well as 3 more labels generated by napari workflows (different thresholds, less accurate segmentations). It also contains 7 tables: The region of interests like in the 3D data, as well as measurements performed with <a href="https://github.com/haesleinhuepf/napari-skimage-regionprops">napari-skimage-regionprops</a>.</p> <p>The tables are stored in the OME-Zarr file according to the <a href="https://fractal-analytics-platform.github.io/fractal-tasks-core/tables/">Fractal table specification</a> spec in AnnData.</p> <p>The 3 channels are:</p> <p>- 0: DAPI, nuclear stain</p> <p>- 1: nanog, antibody staining with Bio-Techne AG, AF1997-SP, Lot KKJ0617121 for the stemness marker nanog</p> <p>- 2: Lamin B1, antibody staining with Abcam, ab16048, Lot GR3244890-2 for the nuclear envelope marker Lamin B1</p>
OME-Zarr hiPSC 3D immunofluorescence images, tiny test set
<p><em>This dataset is intended to be used for automated testing of OME-Zarr processing.</em></p> <p> </p> <p>Example dataset of human induced pluripotent stem cells, imaged at 40x magnification with a Yokogawa CV7000. This is a tiny subset of a larger experiment intended as a test dataset for the <a href="https://fractal-analytics-platform.github.io/">Fractal platform</a> and others experimenting with OME-Zarrs.</p> <p>1 Channel is included:</p> <ul> <li>C01: DAPI, nuclear stain</li> </ul> <p>It is generated from this raw data: <a href="../records/8287221">https://zenodo.org/records/8287221</a></p> <p>This dataset contains 2 Z levels for 2 field of views for this 1 channel, as well as (manually adjusted) metadata files from the Yokogawa CV7000. The data was acquired in the Pelkmans lab in August 2020.</p> <p>The images have been processed using Fractal, the workflow is attached as a json file. It ran with fractal-server==2.3.6, fractal-client==2.0.1, fractal-web==1.4.0 and fractal-tasks-core==1.2.1.</p> <p>Two versions of the OME-Zarr are added here: A 3D version with both Z planes. And a 2D version (MIP of the Z-planes) which also contains label images from cellpose segmentation, measurements and output ROI tables.</p>
OME-Zarr 3D hiPSCs with labels & measurements, 2x2 field of views
<p>These are 2 small OME-Zarr files of the data from <a href="https://doi.org/10.5281/zenodo.7057076">10.5281/zenodo.7057076</a>.</p> <p>They have been processed using <a href="https://pypi.org/project/fractal-client/">fractal-client</a> 0.2.1, <a href="https://pypi.org/project/fractal-server/0.1.2/">fractal-server</a> 0.1.4 and <a href="https://pypi.org/project/fractal-tasks-core/">fractal-tasks-core</a> 0.1.9 using this workflow: <a href="https://github.com/fractal-analytics-platform/fractal/tree/main/examples/08_cardio_2x2_dataset_processing_zenodo">https://github.com/fractal-analytics-platform/fractal/tree/main/examples/08_cardio_2x2_dataset_processing_zenodo</a></p> <p>Both Zarr files are Zip-compressed to allow easier upload & download from Zenodo. </p> <p>20200812-CardiomyocyteDifferentiation14-Cycle1.zarr contains 3 3D channels and a table with regions of interest for the 4 field of views contained in this data.</p> <p>20200812-CardiomyocyteDifferentiation14-Cycle1_mip.zarr contains the same 3 channels, but as maximum intensity projections. It contains nuclear segmentation through cellpose. It also contains 2 tables: The region of interests like in the 3D data, as well as measurements performed with <a href="https://github.com/haesleinhuepf/napari-skimage-regionprops">napari-skimage-regionprops</a>.</p> <p>The tables are stored in the OME-Zarr file according to the <a href="https://github.com/ome/ngff/pull/64">proposed OME-NGFF</a> table spec in AnnData.</p> <p>The 3 channels are:</p> <p>- 0: DAPI, nuclear stain</p> <p>- 1: nanog, antibody staining with Bio-Techne AG, AF1997-SP, Lot KKJ0617121 for the stemness marker nanog</p> <p>- 2: Lamin B1, antibody staining with Abcam, ab16048, Lot GR3244890-2 for the nuclear envelope marker Lamin B1</p> <p> </p> <p>This updated version now passes the ngff schema validation. A version with 3D segmentation is available here: <a href="https://zenodo.org/record/7144919">https://zenodo.org/record/7144919</a></p>
Organoid tiny dataset for stitching (SearchFirst, ome-zarr)
<p>Ome-zarr dataset that is the output of raw tifs (doi <a href="../doi/10.5281/zenodo.12795728">10.5281/zenodo.12795728</a>) processed by Fractal task (see .json file). </p> <p>Dataset acquired on Yokogawa CV8000 on 2024.06.07 by Nicole Repina, Friedrich Miescher Institute for Biomedical Research</p> <p>Dataset contains 11 fields of view (each 1000 x 1000 pix) acquired with SearchFirst*. Touching fields have 50 pix overlap. </p> <p>60x water objective, 2x2 binning, zyx spacing (6, 0.21667, 0.21667) um per pixel. Each field of view has 6 z-slices.</p> <p>Mouse small intestinal organoids (day 4) immunostained with the following dyes (2 fluorescence channels):</p> <p>Channel 1 (C01, 405nm) = DAPI nuclear stain<br>Channel 2 (C02, 488nm) = B-catenin membrane stain</p> <p>*In SearchFirst, the sample is first imaged with a first-pass low-magnification objective (e.g. 4x). An object detection algorithm is then used to identify object-containing regions. Next, the second-pass acquisition is performed with a higher magnification objective that only acquires object-containing regions. The objects are thus imaged not in a tiled grid. Further, some fields may be standalone, while others may have one or more touching fields that are acquired with the specified pixel overlap.</p>
Organoid tiny dataset for stitching (tiled, ome-zarr)
<p>Ome-zarr dataset that is the output of raw tifs (doi <a href="../doi/10.5281/zenodo.12794818">10.5281/zenodo.12794818</a>) processed by Fractal task (see .json file). </p> <p>Dataset acquired on Yokogawa CV8000 on 2023.11.29 by Nicole Repina, Friedrich Miescher Institute for Biomedical Research</p> <p>Dataset contains 3 x 4 (12) tiled fields of view (each 1000 x 1000 pix) acquired with 50 pix overlap. Partial tile (gridded) acquisition.</p> <p>60x water objective, 2x2 binning, zyx spacing (10, 0.21667, 0.21667) um per pixel. Each field of view has 5 z-slices.</p> <p>Mouse small intestinal organoids immunostained with the following dyes (2 fluorescence channels):</p> <p>Channel 1 (C01, 405nm) = DAPI nuclear stain<br>Channel 3 (C03, 568nm) = B-catenin membrane stain</p>
Fractal OME-Zarr Test data for napari-ome-zarr-navigator
<p>Test OME-Zarr data for https://github.com/fractal-analytics-platform/napari-ome-zarr-navigator</p> <p> </p> <p>Contains a 2 HCS OME-Zarrs (2D & 3D) with 2 wells (B03, B05), each with 2 FOVs and the following AnnData tables for each well:</p> <ol> <li>Condition table</li> <li>Feature measurement table</li> <li>2 ROI tables</li> </ol>
Leukemia PDX OME-ZARR
<p>Leukemia cells from a patient-derived xenograft (PDX) model co-cultured with mesenchymal stromal cells. The cells are stained with a viability dye (CyQuant) and imaged on a PerkinElmer Operetta high-content microscope. The OME-ZARR also contains segmentation labels generated by <a href="https://github.com/stardist/stardist">Stardist</a> and measurements with regionprops from <a href="https://scikit-image.org/">scikit-image</a>.</p> <p>The OME-ZARR fileset contains one wells with two fields of view (FOV) with the following perturbation registered in a "condition" table:</p> <ul> <li>C3: DMSO (0.125%)</li> </ul>
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