Add MERSCOPE data conversion script from raw to spatialdata

src/datasets/loaders/vzg_merscope/convert_to_spatialdata.py

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+"""Convert MERSCOPE regions to SpatialData .zarr files.
+
+Produces one .zarr per region with:
+    images:  'morphology_mip'
+    points:  'transcripts'
+    shapes:  'cell_boundaries'  (from cell_boundaries.parquet in region folder)
+    tables:  'table'            (obs × var counts, linked to cell_boundaries)
+    coordinate_systems: 'global'
+"""
+
+import shutil
+from pathlib import Path
+
+import spatialdata as sd
+import yaml
+from spatialdata_io import merscope
+
+# ---------------------------------------------------------------------------
+# Config
+# ---------------------------------------------------------------------------
+with open("metadata.yml") as f:
+    cfg = yaml.safe_load(f)
+
+BASE_DIR = Path(cfg["base_dir"])
+OUTPUT_DIR = Path(cfg["output_dir"])
+REGIONS = cfg["regions"]
+SLIDE_NAME = BASE_DIR.name
+Z_LAYER = cfg["z_layer"]
+DATASET_METADATA = cfg["dataset"]
+
+# ---------------------------------------------------------------------------
+# Load & convert each region
+# ---------------------------------------------------------------------------
+OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+for region in REGIONS:
+    region_dir = BASE_DIR / region
+    dataset_id = f"{SLIDE_NAME}_{region}"
+    print(f"\n{'='*60}")
+    print(f"Processing {region}  (dataset_id={dataset_id})")
+    print(f"{'='*60}")
+
+    # --- Load with spatialdata-io merscope reader ---
+    sdata = merscope(
+        path=region_dir,
+        z_layers=Z_LAYER,
+        region_name=region,
+        slide_name=SLIDE_NAME,
+        backend=None,
+        transcripts=True,
+        cells_boundaries=True,
+        cells_table=True,
+        mosaic_images=True,
+    )
+    print(f"[load] {sdata}")
+
+    # --- Rename elements to canonical names ---
+
+    # Images: {dataset_id}_z{Z_LAYER} → morphology_mip
+    image_key = f"{dataset_id}_z{Z_LAYER}"
+    if image_key in sdata.images:
+        sdata.images["morphology_mip"] = sdata.images.pop(image_key)
+
+    # Points: {dataset_id}_transcripts → transcripts
+    points_key = f"{dataset_id}_transcripts"
+    if points_key in sdata.points:
+        sdata.points["transcripts"] = sdata.points.pop(points_key)
+
+    # Shapes: {dataset_id}_polygons → cell_boundaries
+    polygons_key = f"{dataset_id}_polygons"
+    if polygons_key in sdata.shapes:
+        sdata.shapes["cell_boundaries"] = sdata.shapes.pop(polygons_key)
+
+    # --- Update uns metadata on table ---
+    DATASET_METADATA["dataset_id"] = dataset_id
+    for key, value in DATASET_METADATA.items():
+        sdata.tables["table"].uns[key] = value
+
+    print(f"[done] {sdata}")
+
+    # --- Write output ---
+    out_path = OUTPUT_DIR / f"{region}.zarr"
+    if out_path.exists():
+        shutil.rmtree(out_path)
+    sdata.write(out_path)
+    print(f"[write] {out_path}")
+
+print("\nDone.")

src/datasets/loaders/vzg_merscope/metadata_breastcancer.yml

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+base_dir: "data/BreastCancerTMA/202409242358_240916JHHUBC0005XQ-V2V-HubcTMA-V2-BY_VMSC02511"
+output_dir: "output/BreastCancerTMA"
+regions:
+  - region_R1
+  - region_R2
+  - region_R3
+  - region_R4
+  - region_R5
+z_layer: 3
+
+dataset:
+  dataset_name: "240916JHHUBC0005XQ-V2V-HubcTMA-V2-BY"
+  dataset_url: "https://info.vizgen.com/merfish-2.0-data-release-form"
+  dataset_reference: ""
+  dataset_summary: "MERSCOPE V2 data release."
+  dataset_description: "MERSCOPE V2 data release. Human Breast Cancer TMA FFPE, D2M1774, V2 SOP, cell bond stain"
+  dataset_organism: "Homo sapiens"
+  segmentation_id: "cellpose"

src/datasets/loaders/vzg_merscope/metadata_humanbrain.yml

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+base_dir: "data/HumanBrain/202503211645_HuBrain-FF-22676A1-D2M1769-RC_VMSC16710"
+output_dir: "output/HumanBrain"
+regions:
+  - region_R1
+z_layer: 3
+
+dataset:
+  dataset_name: "HuBrain-FF-22676A1-D2M1769-RC"
+  dataset_url: "https://info.vizgen.com/access-to-merfish-2.0-data-release"
+  dataset_reference: ""
+  dataset_summary: "MERSCOPE V2 Human Brain fresh frozen sample."
+  dataset_description: "MERSCOPE V2 Human Brain fresh frozen, sample 22676A1, panel DM1769, Cellpose segmentation."
+  dataset_organism: "Homo sapiens"
+  segmentation_id: "cellpose"