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xenium tuto WIP
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‎docs/10x_tutorials/xenium_tuto.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[34mINFO \u001b[0m `dims` is specified redundantly: found also inside `data`. \n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[36;20m[INFO] (spatialdata_xenium_explorer.core.images)\u001b[0m Adding image image:\n",
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"<xarray.SpatialImage 'image' (c: 3, y: 43287, x: 22209)>\n",
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"dask.array<rechunk-merge, shape=(3, 43287, 22209), dtype=uint8, chunksize=(1, 4096, 4096), chunktype=numpy.ndarray>\n",
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"Coordinates:\n",
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" * c (c) <U1 '0' '1' '2'\n",
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" * y (y) float64 0.5 1.5 2.5 3.5 ... 4.328e+04 4.329e+04 4.329e+04\n",
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" * x (x) float64 0.5 1.5 2.5 3.5 ... 2.221e+04 2.221e+04 2.221e+04\n",
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"Attributes:\n",
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" transform: {'global': Affine (x, y -> x, y)\\n [1.83698152e-03 6.44010...\n"
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]
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},
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{
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"ename": "KeyError",
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"evalue": "'Image Xeniumranger_V1_hSkin_Melanoma_Add_on_FFPE_he_image already exists in the dataset.'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[31], line 6\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# where you exported the alignment file\u001b[39;00m\n\u001b[1;32m 4\u001b[0m alignment_matrix_path \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mXeniumranger_V1_hSkin_Melanoma_Add_on_FFPE_he_imagealignment.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 6\u001b[0m \u001b[43mspatialdata_xenium_explorer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43malign\u001b[49m\u001b[43m(\u001b[49m\u001b[43msdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mh_and_e\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43malignment_matrix_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mimage_key\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mimage_key\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/dev/spatialdata_xenium_explorer/spatialdata_xenium_explorer/core/images.py:243\u001b[0m, in \u001b[0;36malign\u001b[0;34m(sdata, image, transformation_matrix_path, image_key, image_models_kwargs, overwrite)\u001b[0m\n\u001b[1;32m 234\u001b[0m image \u001b[38;5;241m=\u001b[39m Image2DModel\u001b[38;5;241m.\u001b[39mparse(\n\u001b[1;32m 235\u001b[0m image,\n\u001b[1;32m 236\u001b[0m dims\u001b[38;5;241m=\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mc\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mimage_models_kwargs,\n\u001b[1;32m 240\u001b[0m )\n\u001b[1;32m 242\u001b[0m log\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAdding image \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mimage\u001b[38;5;241m.\u001b[39mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mimage\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m--> 243\u001b[0m \u001b[43msdata\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madd_image\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimage_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mimage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moverwrite\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moverwrite\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/spatialdata-xenium-explorer-yAxRBYoR-py3.9/lib/python3.9/site-packages/spatialdata/_core/spatialdata.py:710\u001b[0m, in \u001b[0;36mSpatialData.add_image\u001b[0;34m(self, name, image, storage_options, overwrite)\u001b[0m\n\u001b[1;32m 708\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_add_image_in_memory(name\u001b[38;5;241m=\u001b[39mname, image\u001b[38;5;241m=\u001b[39mimage, overwrite\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 709\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 710\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_add_image_in_memory\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mimage\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mimage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moverwrite\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moverwrite\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/spatialdata-xenium-explorer-yAxRBYoR-py3.9/lib/python3.9/site-packages/spatialdata/_core/spatialdata.py:288\u001b[0m, in \u001b[0;36mSpatialData._add_image_in_memory\u001b[0;34m(self, name, image, overwrite)\u001b[0m\n\u001b[1;32m 284\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_unique_element_names(\n\u001b[1;32m 285\u001b[0m \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlabels\u001b[38;5;241m.\u001b[39mkeys()) \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpoints\u001b[38;5;241m.\u001b[39mkeys()) \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mshapes\u001b[38;5;241m.\u001b[39mkeys()) \u001b[38;5;241m+\u001b[39m [name]\n\u001b[1;32m 286\u001b[0m )\n\u001b[1;32m 287\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_images \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m overwrite:\n\u001b[0;32m--> 288\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mImage \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m already exists in the dataset.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 289\u001b[0m ndim \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(get_axes_names(image))\n\u001b[1;32m 290\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m3\u001b[39m:\n",
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"\u001b[0;31mKeyError\u001b[0m: 'Image Xeniumranger_V1_hSkin_Melanoma_Add_on_FFPE_he_image already exists in the dataset.'"
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]
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}
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],
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"outputs": [],
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"source": [
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"image_key = \"morphology_mip\"\n",
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"\n",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Alignment from `SpatialData` to the Xenium Explorer"
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"### Alignment from `SpatialData` to the Xenium Explorer\n",
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"\n",
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"Now, we suppose you have already aligned your H&E image using `SpatialData`. Here, we detail how use the transformation inside the Xenium Explorer."
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"import numpy as np"
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, we get the transformation from the H&E image to the global coordinate system:"
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]
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},
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"cell_type": "code",
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"transformation = get_transformation(spatial_element, to_coordinate_system=\"global\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"If it is an affine transformation, we can create a `.csv` file representing the transformation:"
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},
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"cell_type": "code",
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"execution_count": 30,
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"metadata": {},
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"source": [
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"assert isinstance(transformation, Affine), \"The Xenium Explorer only supports Affine transformations\"\n",
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"assert isinstance(\n",
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" transformation, Affine\n",
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"), \"The Xenium Explorer only supports Affine transformations\"\n",
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"\n",
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"np.savetxt(\"alignment_matrix.csv\", transformation.matrix, delimiter=\",\")"
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"# 4. Update the cells on the Explorer\n",
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"### Update the cell categories"
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"### Update the cell categories\n",
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"\n",
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"Here, we run some Leiden clustering with `scanpy`. Then, we will update the Xenium Explorer files to display the spot clusters.\n",
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"\n",
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"More generally, you can add new cell categories, i.e. a column of `sdata.table.obs`, and the Xenium Explorer will show it after the instructions below.\n",
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"\n",
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"> Note that we only display categorical columns. If a column from `sdata.table.obs` contains continuous numerical values (e.g., `3.13, 7.89, ...`), it will not be transformed into a categorical variable, and therefore not shown in the Xenium Explorer. In this case, we recommend using `spatiadata_plot` as shown above."
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"### Update a new segmentation\n",
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"\n",
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"In the case where you performed your own segmentation, you may want to update the explorer with your new cells.\n",
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"In the case where you performed your own segmentation, you may want to update the explorer with your new cells. You'll also need to update `sdata.table` to contain the transcript counts associated to your new cells.\n",
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"\n",
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"> Note that `mode=\"-it\"` signifies to create all files except the image and transcript file. Indeed, the two latter files doesn't need to be updated, they will remain the same."
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"# this is the key related to your new cell boundaries, i.e. sdata[shapes_key] is a pandas GeoDataFrame\n",
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"shapes_key = \"new_shapes\"\n",
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"\n",
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"spatialdata.aggregate(...)"
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"shapes_key = \"new_shapes\""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now, update all the files related to your new cells:"
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{

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