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Support Baysor>=7.0.0 #127

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merged 6 commits into from
Sep 25, 2024
Merged

Support Baysor>=7.0.0 #127

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575bfdb
Fix compatibility with latest version of Baysor
lguerard Sep 24, 2024
69f048e
Fix issue with WindowPath and glob
lguerard Sep 24, 2024
b05e3ce
Revert last commit and update API documentation
lguerard Sep 24, 2024
938b7db
Fix parsing of Cell number from loom file
lguerard Sep 24, 2024
9b58d3d
Merge branch 'dev' of https://github.com/lguerard/sopa into lguerard-dev
quentinblampey Sep 25, 2024
ba537a3
check whether the cell ids are string or int
quentinblampey Sep 25, 2024
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60 changes: 34 additions & 26 deletions docs/tutorials/api_usage.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -78,8 +78,10 @@
"outputs": [],
"source": [
"image_key = \"image\"\n",
"points_key = \"transcripts\" # (ignore this for multiplex imaging)\n",
"gene_column = \"genes\" # (optional) column of sdata[points_key] containing the gene names"
"points_key = \"transcripts\" # (ignore this for multiplex imaging)\n",
"gene_column = (\n",
" \"genes\" # (optional) column of sdata[points_key] containing the gene names\n",
")"
]
},
{
Expand Down Expand Up @@ -117,7 +119,9 @@
}
],
"source": [
"patches = sopa.segmentation.Patches2D(sdata, image_key, patch_width=1200, patch_overlap=50)\n",
"patches = sopa.segmentation.Patches2D(\n",
" sdata, image_key, patch_width=1200, patch_overlap=50\n",
")\n",
"patches.write();"
]
},
Expand Down Expand Up @@ -163,8 +167,12 @@
"source": [
"channels = [\"DAPI\"]\n",
"\n",
"method = sopa.segmentation.methods.cellpose_patch(diameter=35, channels=channels, flow_threshold=2, cellprob_threshold=-6)\n",
"segmentation = sopa.segmentation.StainingSegmentation(sdata, method, channels, min_area=2500)\n",
"method = sopa.segmentation.methods.cellpose_patch(\n",
" diameter=35, channels=channels, flow_threshold=2, cellprob_threshold=-6\n",
")\n",
"segmentation = sopa.segmentation.StainingSegmentation(\n",
" sdata, method, channels, min_area=2500\n",
")\n",
"\n",
"# The cellpose boundaries will be temporary saved here. You can choose a different path\n",
"cellpose_temp_dir = \"tuto.zarr/.sopa_cache/cellpose\""
Expand Down Expand Up @@ -231,7 +239,7 @@
],
"source": [
"# parallelize this for loop yourself (or use the Snakemake pipeline)\n",
"for patch_index in range(len(sdata['sopa_patches'])):\n",
"for patch_index in range(len(sdata[\"sopa_patches\"])):\n",
" segmentation.write_patch_cells(cellpose_temp_dir, patch_index)"
]
},
Expand Down Expand Up @@ -269,7 +277,7 @@
"cells = sopa.segmentation.StainingSegmentation.read_patches_cells(cellpose_temp_dir)\n",
"cells = sopa.segmentation.shapes.solve_conflicts(cells)\n",
"\n",
"shapes_key = \"cellpose_boundaries\" # name of the key given to the cells in sdata.shapes\n",
"shapes_key = \"cellpose_boundaries\" # name of the key given to the cells in sdata.shapes\n",
"\n",
"sopa.segmentation.StainingSegmentation.add_shapes(sdata, cells, image_key, shapes_key)"
]
Expand All @@ -287,7 +295,7 @@
"metadata": {},
"outputs": [],
"source": [
"shapes_key = \"baysor_boundaries\" # the name that we will give to the baysor \"shapes\""
"shapes_key = \"baysor_boundaries\" # the name that we will give to the baysor \"shapes\""
]
},
{
Expand Down Expand Up @@ -317,7 +325,7 @@
" \"gene\": \"genes\",\n",
" \"min_molecules_per_gene\": 0,\n",
" \"min_molecules_per_segment\": 3,\n",
" \"confidence_nn_id\": 6\n",
" \"confidence_nn_id\": 6,\n",
" },\n",
" \"segmentation\": {\n",
" \"scale\": 3, # Important parameter: typical cell diameter, in microns (see our configs)\n",
Expand All @@ -329,9 +337,7 @@
" \"n_cells_init\": 0,\n",
" \"nuclei_genes\": \"\",\n",
" \"cyto_genes\": \"\",\n",
" \"new_component_weight\": 0.2,\n",
" \"new_component_fraction\": 0.3\n",
" }\n",
" },\n",
"}"
]
},
Expand Down Expand Up @@ -373,7 +379,9 @@
"# The cellpose boundaries will be temporary saved here. You can choose a different path\n",
"baysor_temp_dir = \"tuto.zarr/.sopa_cache/baysor\"\n",
"\n",
"patches = sopa.segmentation.Patches2D(sdata, points_key, patch_width=3000, patch_overlap=50)\n",
"patches = sopa.segmentation.Patches2D(\n",
" sdata, points_key, patch_width=3000, patch_overlap=50\n",
")\n",
"valid_indices = patches.patchify_transcripts(baysor_temp_dir, config=config)"
]
},
Expand Down Expand Up @@ -409,7 +417,7 @@
"for patch_index in valid_indices:\n",
" command = f\"\"\"\n",
" cd {baysor_temp_dir}/{patch_index}\n",
" {baysor_executable_path} run --save-polygons GeoJSON -c config.toml transcripts.csv\n",
" {baysor_executable_path} run --polygon-format=GeometryCollection -c config.toml transcripts.csv\n",
" \"\"\"\n",
" subprocess.run(command, shell=True)"
]
Expand Down Expand Up @@ -501,7 +509,9 @@
}
],
"source": [
"aggregator = sopa.segmentation.Aggregator(sdata, image_key=image_key, shapes_key=shapes_key)\n",
"aggregator = sopa.segmentation.Aggregator(\n",
" sdata, image_key=image_key, shapes_key=shapes_key\n",
")\n",
"\n",
"aggregator.compute_table(gene_column=gene_column, average_intensities=True)"
]
Expand Down Expand Up @@ -611,11 +621,7 @@
"source": [
"from sopa.annotation import higher_z_score\n",
"\n",
"marker_cell_dict = {\n",
" \"CK\": \"Tumoral cell\",\n",
" \"CD20\": \"B cell\",\n",
" \"CD3\": \"T cell\"\n",
"}\n",
"marker_cell_dict = {\"CK\": \"Tumoral cell\", \"CD20\": \"B cell\", \"CD3\": \"T cell\"}\n",
"\n",
"higher_z_score(sdata.tables[\"table\"], marker_cell_dict)"
]
Expand Down Expand Up @@ -698,7 +704,9 @@
}
],
"source": [
"sopa.io.write(\"tuto.explorer\", sdata, image_key, points_key=points_key, gene_column=gene_column)"
"sopa.io.write(\n",
" \"tuto.explorer\", sdata, image_key, points_key=points_key, gene_column=gene_column\n",
")"
]
},
{
Expand Down Expand Up @@ -767,11 +775,11 @@
}
],
"source": [
"sdata\\\n",
" .pl.render_points(size=0.01, color=\"r\", alpha=0.5)\\\n",
" .pl.render_images()\\\n",
" .pl.render_shapes(shapes_key, outline=True, fill_alpha=0, outline_color=\"w\")\\\n",
" .pl.show(\"global\")"
"sdata.pl.render_points(\n",
" size=0.01, color=\"r\", alpha=0.5\n",
").pl.render_images().pl.render_shapes(\n",
" shapes_key, outline=True, fill_alpha=0, outline_color=\"w\"\n",
").pl.show(\"global\")"
]
},
{
Expand Down
19 changes: 16 additions & 3 deletions sopa/segmentation/transcripts.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -97,6 +97,7 @@ def _read_one_segmented_patch(
directory: str, min_area: float = 0, min_vertices: int = 4
) -> tuple[list[Polygon], AnnData]:
directory: Path = Path(directory)
id_as_string, polygon_file = _find_polygon_file(directory)

loom_file = directory / "segmentation_counts.loom"
if loom_file.exists():
Expand All @@ -106,16 +107,19 @@ def _read_one_segmented_patch(

adata.obs.rename(columns={"area": SopaKeys.ORIGINAL_AREA_OBS}, inplace=True)

cells_num = pd.Series(adata.obs["CellID"].astype(int), index=adata.obs_names)
cells_num = pd.Series(adata.obs_names if id_as_string else adata.obs["CellID"].astype(int), index=adata.obs_names)
del adata.obs["CellID"]

with open(directory / "segmentation_polygons.json") as f:
with open(polygon_file) as f:
polygons_dict = json.load(f)
polygons_dict = {c["cell"]: c for c in polygons_dict["geometries"]}

cells_num = cells_num[cells_num.map(lambda num: len(polygons_dict[num]["coordinates"][0]) >= min_vertices)]

gdf = gpd.GeoDataFrame(index=cells_num.index, geometry=[shape(polygons_dict[cell_num]) for cell_num in cells_num])
gdf = gpd.GeoDataFrame(
index=cells_num.index,
geometry=[shape(polygons_dict[cell_num]) for cell_num in cells_num],
)

gdf.geometry = gdf.geometry.map(lambda cell: shapes._ensure_polygon(cell))
gdf = gdf[~gdf.geometry.isna()]
Expand All @@ -129,6 +133,15 @@ def _read_one_segmented_patch(
return gdf.geometry.values, adata[gdf.index].copy()


def _find_polygon_file(directory: Path) -> tuple[bool, Path]:
old_baysor_path = directory / "segmentation_polygons.json"
if old_baysor_path.exists():
return False, old_baysor_path
new_baysor_path = directory / "segmentation_polygons_2d.json"
assert new_baysor_path.exists(), f"Could not find the segmentation polygons file in {directory}"
return True, new_baysor_path


def _read_all_segmented_patches(
temp_dir: str,
min_area: float = 0,
Expand Down
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