Technology Focus: 10x Genomics Xenium (Simplified)#
This tutorial highlights the basic functions of SegTraQ on a single Xenium dataset that was segmented using the Xenium default segmentation. To follow along, you can download the data already in SpatialData format from here.
For a more detailed description of how the data was obtained and a comparison between segmentation methods, please look at the Xenium Focus.
Read SpatialData object#
[1]:
%load_ext autoreload
%autoreload 2
[2]:
import warnings
import anndata as ad
import dask
import matplotlib.pyplot as plt
import pandas as pd
import scanpy as sc
import seaborn as sns
import spatialdata as sd
import spatialdata_plot # noqa
import segtraq
# filtering import and deprecation warnings from spatialdata
# this is in general not recommended
# we only do it here because we have verified that the warnings are irrelevant in this notebook
warnings.simplefilter("ignore", FutureWarning)
warnings.simplefilter("ignore", UserWarning)
warnings.filterwarnings(
"ignore",
category=FutureWarning,
module=r"dask\.dataframe",
)
warnings.filterwarnings(
"ignore",
category=FutureWarning,
module=r"spatialdata\._core\.query\.relational_query",
)
dask.config.set({"dataframe.query-planning": True})
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
[2]:
<dask.config.set at 0x7fecbb7834d0>
[3]:
sdata = sd.read_zarr("../../data/xenium_5K_data/xenium.zarr")
no parent found for <ome_zarr.reader.Label object at 0x7fecad1bf4d0>: None
no parent found for <ome_zarr.reader.Label object at 0x7fecad213ed0>: None
Let’s have a quick look at the data.
[4]:
sdata.pl.render_shapes("cell_boundaries").pl.show()
INFO Using 'datashader' backend with 'None' as reduction method to speed up plotting. Depending on the
reduction method, the value range of the plot might change. Set method to 'matplotlib' to disable this
behaviour.
Initialize SegTraQ objects#
Next, we initialize a SegTraQ object. The reason for this is that different technologies call things differently: cell centroids could be called centroid_x, x_centroid, cell_x, … By initializing a SegTraQ object, we only have to tell SegTraQ where our data lives once.
Don’t worry if you do not know which parameters you need up front; just put in your spatialdata object (segtraq.SegTraQ(sdata)), and SegTraQ will tell you which arguments are wrong/missing.
[5]:
st = segtraq.SegTraQ(
sdata,
images_key="image", # where the image is stored
tables_centroid_x_key="x_centroid", # where the x centroid is stored
tables_centroid_y_key="y_centroid", # where the y centroid is stored
)
Now the data is ready to compute some quality control metrics. SegTraQ is structured into different modules, all of which focus on different problems that can arise during segmentation. We will now go through all of the modules and look at what they tell us about our segmentation.
Baseline module#
The baseline (bl) module computes basic quality-control metrics such as the number of cells, the percentage of unassigned transcripts, and the number of transcripts and genes per cell. All of the results that SegTraQ computes are automatically stored in your spatialdata object.
[6]:
# the number of cells
st.bl.num_cells()
[6]:
18311
[7]:
# the percentage of transcripts not assigned to any cell
st.bl.perc_unassigned_transcripts()
[7]:
9.96496475097772
[8]:
# the number of transcripts per cell
st.bl.transcripts_per_cell().head()
[8]:
| cell_id | transcript_count | |
|---|---|---|
| 0 | afbommff-1 | 1751 |
| 1 | afbihifc-1 | 1652 |
| 2 | afbjnaja-1 | 1636 |
| 3 | afjdkagk-1 | 1462 |
| 4 | afblgimd-1 | 1402 |
[9]:
# the number of genes per cell
st.bl.genes_per_cell().head()
[9]:
| cell_id | gene_count | |
|---|---|---|
| 0 | acceakgj-1 | 102 |
| 1 | accebped-1 | 109 |
| 2 | accedpdh-1 | 56 |
| 3 | acceejoe-1 | 65 |
| 4 | acceekkh-1 | 57 |
[10]:
# the mean number of transcripts per gene per cell
st.bl.mean_transcripts_per_gene_per_cell().head()
[10]:
| cell_id | mean_transcripts_per_gene | |
|---|---|---|
| 0 | acceakgj-1 | 1.225490 |
| 1 | accebped-1 | 1.587156 |
| 2 | accedpdh-1 | 1.375000 |
| 3 | acceejoe-1 | 1.430769 |
| 4 | acceekkh-1 | 1.210526 |
We can also compute some morphological features of the cells using bl.morphological_features().
[11]:
st.bl.morphological_features().head()
[11]:
| cell_id | cell_area | perimeter | circularity | bbox_width | bbox_height | extent | solidity | convexity | elongation | eccentricity | compactness | num_polygons | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | acceakgj-1 | 45.630318 | 25.596593 | 0.875183 | 8.074951 | 7.862305 | 0.718727 | 0.974460 | 0.983536 | 1.097515 | 0.412076 | 14.358558 | 1 |
| 1 | accebped-1 | 44.433013 | 25.224078 | 0.877577 | 8.500000 | 7.012695 | 0.745421 | 0.969899 | 0.983684 | 1.377976 | 0.688009 | 14.319400 | 1 |
| 2 | accedpdh-1 | 46.737367 | 26.267438 | 0.851214 | 9.350098 | 6.587891 | 0.758755 | 0.964090 | 0.984115 | 1.367124 | 0.681882 | 14.762883 | 1 |
| 3 | acceejoe-1 | 33.030204 | 22.242175 | 0.839009 | 6.587646 | 7.011719 | 0.715083 | 0.968244 | 0.978508 | 1.214174 | 0.567164 | 14.977635 | 1 |
| 4 | acceekkh-1 | 40.730569 | 23.923744 | 0.894277 | 7.862549 | 7.862305 | 0.658881 | 0.982569 | 0.987680 | 1.117125 | 0.445754 | 14.051989 | 1 |
Clustering stability module#
The clustering stability (cs) module provides metrics for assessing the stability of clustering results across different clustering resolutions and random subsets of genes. The idea is as follows: the better a segmentation method separates cell types, the better it is. We can compute a couple of metrics to investigate this.
Let`s first perform Leiden clustering and visualize the clusters in the UMAP space.
[12]:
# extracting the anndata object from the spatialdata object and performing appropriate normalization
adata = st.sdata.tables["table"]
adata.layers["counts"] = adata.X.copy()
sc.pp.normalize_total(adata, inplace=True)
sc.pp.log1p(adata)
sc.pp.pca(adata)
sc.pp.neighbors(adata)
sc.tl.umap(adata)
sc.tl.leiden(adata, flavor="igraph", n_iterations=2)
# plotting the result of the leiden clustering
sc.pl.umap(adata, color="leiden")
We can start by looking at the cluster connectedness. To compute it, we use the neighborhood graph we computed with scanpy earlier. The method then iterates over all cells and computes the number of neighbors with the same cluster assignment and divides it by the number of total neighbors. In general, the higher this value is, the better. To make this not too dependent on the resolution of the Leiden clustering, this is done with three different resolutions (0.6, 0.8, 1.0), and the best value is returned.
[13]:
st.cs.cluster_connectedness()
[13]:
0.8157400360790642
We can do the same with the silhouette score.
[14]:
st.cs.silhouette_score()
[14]:
-0.005692636594176292
Next, we can check how stable the clustering is when we only take a subset (63%) of our genes and run clustering on this. We do this five times, and then assess the quality with the adjusted Rand index (ARI) and the purity. For more details on these metrics, refer to the section on this module.
[15]:
st.cs.adjusted_rand_index()
[15]:
0.6141074498534771
[16]:
st.cs.purity()
[16]:
0.7632044929420014
Region similarity module#
While individual genes may exhibit subcellular localization patterns, the overall distribution of transcripts, when averaged across genes, is expected to be relatively smooth and approximately uniform within a cell. Based on this assumption, the region similarity module evaluates the similarity of gene expression profiles across different subcellular compartments. Deviations from this expected intra-cellular consistency can serve as indicators of transcript contamination originating from neighboring cells.
Similarity between nucleus and cytoplasm#
First, we look at the correlation between a cell’s nucleus and the rest of the cell. A high similarity here means that there is littly contamination, whereas a low correlation can hint towards spillover from adjacent cells.
[17]:
st.rs.similarity_nucleus_cytoplasm().head()
[17]:
| cell_id | nucleus_id | iou | nucleus_fraction | similarity_nucleus_cytoplasm | |
|---|---|---|---|---|---|
| 0 | acceakgj-1 | 0.0 | 0.617026 | 1.000000 | 0.050798 |
| 1 | accebped-1 | 1.0 | 0.556906 | 0.999997 | 0.042276 |
| 2 | accedpdh-1 | 2.0 | 0.427579 | 0.997749 | 0.044994 |
| 3 | acceejoe-1 | 3.0 | 0.708851 | 1.000000 | NaN |
| 4 | acceekkh-1 | 4.0 | 0.543778 | 1.000000 | 0.035391 |
Similarity between a cell’s border the cellular neighborhood#
Next to that, we can also compute the similarity between a cells outer shell (transcripts close to the cell membrane) and its surrounding cells (which we call the Neighborhood Composition Vector (NCV) here). A high similarity here can indicate spillover.
[18]:
st.rs.similarity_border_neighborhood().head()
[18]:
| cell_id | similarity_center_border | similarity_border_neighborhood | ratio_border_neighborhood_to_center | |
|---|---|---|---|---|
| 0 | acceakgj-1 | 0.091307 | 0.090502 | 0.991186 |
| 1 | accebped-1 | 0.125517 | 0.094898 | 0.756057 |
| 2 | accedpdh-1 | 0.189379 | 0.060705 | 0.320548 |
| 3 | acceejoe-1 | 0.086407 | 0.160666 | 1.859408 |
| 4 | acceekkh-1 | 0.143825 | 0.094464 | 0.656798 |
Supervised module#
The sp (supervised) module provides metrics to evaluate how well cell profiles in a spatial transcriptomics dataset agree with a reference single-cell RNA-seq (scRNA-seq) dataset with cell type annotations.
Unlike scRNA-seq, contamination in spatial transcriptomics measurements mostly originates from the local tissue context.
By comparing spatial expression profiles to a high-quality scRNA-seq reference, the supervised module aims to quantify this mismatch. Specifically, we compute metrics that measure:
how well each spatial cell matches its expected cell type,
how much its expression resembles other (neighboring) cell types, and
if it is possible to predict that a cell of one cell type is adjacent to a different cell type.
To obtain cell-type specific marker genes, we define positive and negative markers in the annotated scRNA-seq via markers_from_reference.
[19]:
adata_ref = ad.read_h5ad("../../data/xenium_5K_data/BC_scRNAseq_Janesick.h5ad")
Computing cell-type specific markers#
[20]:
# hiding all warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
tbl = st.sdata["table"]
common_genes = tbl.var_names[tbl.var_names.isin(adata_ref.var_names)]
adata_ref = adata_ref[:, common_genes].copy()
markers = segtraq.markers_from_reference(
adata_ref,
cell_type_key="celltype_major",
n_jobs=16,
)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:531: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left = partial(_left_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:532: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
left_exclusive = partial(_left_exclusive_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:533: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
inner = partial(_inner_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:534: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right = partial(_right_join_spatialelement_table)
/g/huber/users/meyerben/notebooks/spatial_transcriptomics/SegTraQ/.venv/lib/python3.13/site-packages/spatialdata/_core/query/relational_query.py:535: FutureWarning: functools.partial will be a method descriptor in future Python versions; wrap it in enum.member() if you want to preserve the old behavior
right_exclusive = partial(_right_exclusive_join_spatialelement_table)
Below, we show the number of negative markers that overlap with the positive markers of each cell type.
To reliably estimate contamination, each cell type should share at least ~5 negative markers with the positive marker set of every other cell type. If these overlaps are too small, contamination estimates become unstable.
In such cases, the marker definition can be relaxed by adjusting the thresholds used in markers_from_reference above.
[21]:
ctypes = list(markers.keys())
overlap_df = pd.DataFrame(0, index=ctypes, columns=ctypes, dtype=int)
for c in ctypes:
neg_c = set(markers[c].get("negative", []))
for d in ctypes:
pos_d = set(markers[d].get("positive", []))
overlap_df.loc[c, d] = len(neg_c & pos_d)
overlap_df
[21]:
| B | DCIS1 | DCIS2 | T | dendritic | endo | macro | mast | myoepi | perivas | stromal | tumor | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| B | 0 | 58 | 74 | 25 | 43 | 128 | 89 | 23 | 139 | 53 | 101 | 119 |
| DCIS1 | 45 | 0 | 16 | 47 | 59 | 98 | 79 | 26 | 44 | 42 | 66 | 26 |
| DCIS2 | 43 | 11 | 0 | 50 | 58 | 102 | 82 | 25 | 63 | 44 | 73 | 5 |
| T | 34 | 137 | 156 | 0 | 70 | 149 | 132 | 28 | 157 | 61 | 115 | 269 |
| dendritic | 27 | 55 | 76 | 28 | 0 | 115 | 59 | 19 | 123 | 47 | 84 | 127 |
| endo | 41 | 43 | 43 | 38 | 43 | 0 | 73 | 22 | 60 | 4 | 31 | 76 |
| macro | 25 | 48 | 61 | 17 | 32 | 104 | 0 | 16 | 99 | 50 | 78 | 99 |
| mast | 35 | 148 | 172 | 38 | 65 | 127 | 99 | 0 | 124 | 42 | 96 | 298 |
| myoepi | 41 | 8 | 4 | 33 | 47 | 59 | 47 | 18 | 0 | 27 | 37 | 22 |
| perivas | 45 | 50 | 55 | 30 | 48 | 51 | 91 | 25 | 75 | 0 | 41 | 89 |
| stromal | 44 | 43 | 42 | 47 | 48 | 65 | 57 | 24 | 63 | 20 | 0 | 83 |
| tumor | 47 | 21 | 9 | 58 | 62 | 109 | 100 | 27 | 91 | 45 | 82 | 0 |
Label transfer#
Before we can do statistics on the spatial data, we first need to transfer our cell type labels onto the spatial transcriptomics data. We can do this simply by calling run_label_transfer().
[22]:
st.run_label_transfer(adata_ref, ref_cell_type="celltype_major", ref_ensemble_key=None, query_ensemble_key=None)
Let’s quickly verify that this worked by plotting the data.
[23]:
# Replace NaN with Unknown for plotting
s = st.sdata.tables["table"].obs["transferred_cell_type"]
if pd.api.types.is_categorical_dtype(s):
s = s.cat.add_categories(["Unknown"])
st.sdata.tables["table"].obs["transferred_celltype_plot"] = s.fillna("Unknown")
# before we can plot, we need to link the shapes to the table
st.sdata.tables["table"].obs["region"] = "cell_boundaries"
st.sdata.set_table_annotates_spatialelement("table", region="cell_boundaries")
[24]:
st.sdata.pl.render_shapes("cell_boundaries", color="transferred_celltype_plot").pl.show(coordinate_systems="global")
INFO Using 'datashader' backend with 'None' as reduction method to speed up plotting. Depending on the
reduction method, the value range of the plot might change. Set method to 'matplotlib' to disable this
behaviour.
Marker purity#
To quantify how well each segmented cell in the spatial transcriptomics data matches its annotated cell type, we defined a marker-based purity (F1_purity) score that jointly evaluates the expression of positive (positive_F1) and the absence of neighborhood-associated negative markers (negative_F1). The method accounts for the spatial context of each cell and is motivated by the assumption that differences between scRNA-seq and spatial transcriptomics-derived cell type profiles arise
mainly from local contamination by neighboring cells.
[25]:
st.sp.marker_purity(cell_type_key="transferred_cell_type", markers=markers).head()
INFO Creating graph using `generic` coordinates and `None` transform and `1` libraries.
[25]:
| positive_precision | positive_recall | positive_F1 | negative_precision | negative_recall | negative_F1 | F1_purity | |
|---|---|---|---|---|---|---|---|
| cell_id | |||||||
| acceakgj-1 | 0.384615 | 0.049505 | 0.087719 | 0.000000 | 0.0 | 0.000000 | 0.726316 |
| accebped-1 | 0.437500 | 0.069307 | 0.119658 | 0.083333 | 0.2 | 0.117647 | 0.653544 |
| accedpdh-1 | 0.750000 | 0.020000 | 0.038961 | 0.000000 | 0.0 | 0.000000 | 0.711688 |
| acceejoe-1 | 0.777778 | 0.069307 | 0.127273 | 0.000000 | 0.0 | 0.000000 | 0.738182 |
| acceekkh-1 | 0.538462 | 0.069307 | 0.122807 | 0.000000 | 0.0 | 0.000000 | 0.736842 |
These metrics are most informative when considered jointly. For an example, please refer to the Xenium Focus.
Neighborhood contamination#
Marker purity summarizes how well a cell matches its own markers and avoids neighborhood-relevant negatives. In many cases, we also want to quantify (i) how many contaminating transcripts are present per cell and (ii) which neighboring cell types contribute to this signal. We therefore compute neighborhood contamination.
[26]:
per_cell_df, _, _ = st.sp.neighbor_contamination(cell_type_key="transferred_cell_type", markers=markers)
per_cell_df.head()
[26]:
| negative_marker_contamination_counts | negative_marker_contamination_fraction | |
|---|---|---|
| cell_id | ||
| acceakgj-1 | 0.0 | NaN |
| accebped-1 | 1.0 | 0.333333 |
| accedpdh-1 | 0.0 | NaN |
| acceejoe-1 | 0.0 | NaN |
| acceekkh-1 | 0.0 | NaN |
Finally, the heatmap below shows, for each source–target cell-type pair, the fraction of all target cells contaminated by transcripts from a neighboring source cell type.
Percentages within a column may sum to more than 100% because a single target cell can be contaminated by multiple neighboring source cell types and is therefore counted for each of them.
Sources of contamination differ between methods. The higher contamination in mast cells in Proseg originates mostly from DCIS2 and macrophages, contamination in T cells mostly originates from B cells and in B cells mostly from stromal cells.
[27]:
sns.heatmap(
st.sdata.tables["table"].uns["negative_marker_contamination_binary"],
annot=True,
fmt=".2f",
cmap="Reds",
annot_kws={"size": 5},
cbar=False,
)
plt.xlabel("Target Cell Type")
plt.ylabel("Source Cell Type")
plt.show()
Mutually exclusive co-expression rate (MECR)#
The mutually exclusive co-expression rate (MECR) is a measure for whether combinations of positive and negative markers (computed with a more stringent setting to increase mutual exclusivity, vote_frac_pos=0.3) co-occur less often than expected under independence.
[28]:
tbl = st.sdata["table"]
common_genes = tbl.var_names[tbl.var_names.isin(adata_ref.var_names)]
adata_ref = adata_ref[:, common_genes].copy()
markers = segtraq.markers_from_reference(adata_ref, cell_type_key="celltype_major", min_pos_frac=0.3, n_jobs=16)
st.sp.mutually_exclusive_coexpression_rate(markers=markers).head()
[28]:
| gene1 | gene2 | odds_ratio | pvalue | a | b | c | d | |
|---|---|---|---|---|---|---|---|---|
| 0 | MYBBP1A | SPIB | 1.853667 | 0.846511 | 2 | 217 | 111 | 17981 |
| 1 | CD96 | SLC20A2 | 0.595807 | 0.217649 | 2 | 386 | 192 | 17731 |
| 2 | CNNM3 | EPHB1 | 3.759494 | 0.969635 | 2 | 302 | 39 | 17968 |
| 3 | ENPP3 | GMPS | 2.574859 | 0.976584 | 5 | 67 | 559 | 17680 |
| 4 | TNFRSF6B | TRIM29 | 1.026622 | 0.576127 | 1 | 90 | 289 | 17931 |
3D Volume Module#
The volume (vl) accessor provides metrics to assess how well a segmentation method resolves cell overlaps in 3D. Spatial transcriptomics tissue sections have a finite thickness (~4–10 µm), so cells can overlap along the z-dimension and 2D segmentation methods may introduce mixing by assigning transcripts from overlapping cells to the same mask. In this module, we introduce metrics to quantify sensitivity to 3D overlap and evaluate how well quasi-3D methods (e.g. Proseg) disentangle
transcripts from overlapping cells.
For a detailed description of this module, please refer to this tutorial.
Top-bottom z consistency#
To detect potential z-overlap mixing within segmented cells, we split each cell’s transcripts into bottom/top z-quantiles (q=0.30), compute log-normalized gene profiles for both parts, and report their cosine similarity (NaN if either part has <10 transcripts or <5 genes).
[29]:
st.vl.similarity_top_bottom().head()
[29]:
| cell_id | cosine_sim_top_bottom_z | |
|---|---|---|
| 0 | acceakgj-1 | 0.103205 |
| 1 | accebped-1 | 0.000000 |
| 2 | accedpdh-1 | 0.124975 |
| 3 | acceejoe-1 | 0.051639 |
| 4 | acceekkh-1 | 0.000000 |
In volume.ipynb, we explore the distribution of transcripts along the z-dimension in more depth and put it into context with ovrlpy, a package for detecting 3D overlap in spatial transcriptomics. There, we use a Xenium v1 dataset with a 313-gene panel, where transcript coverage is higher and the analysis is less affected by sparsity.
Point statistic metrics#
The point statistics (ps) module is designed to compare the distribution of a set of transcripts in the cell relative to its cell centroid or cell border. The idea is to compute the distances of the transcripts to a reference point in the cell, either the cell centroid or the cell boundaries and aggregate this measure per transcript id.
Distance of transcripts to the cell membrane#
In this metric we compute the distance to the segmented cell membrane of each transcript coordinate and aggregate this metric per transcript id as mean. For examplease, we can compute both the average distance to the cell membrane across all previously defined negative and positive markers for the cell type “DCIS2”.
[30]:
border_distance_negative = st.ps.distance_to_membrane(
markers["DCIS2"]["negative"],
cell_type_key="transferred_celltype_plot",
cell_type_query=["DCIS2"],
inplace=False,
)
border_distance_positive = st.ps.distance_to_membrane(
markers["DCIS2"]["positive"],
cell_type_key="transferred_celltype_plot",
cell_type_query=["DCIS2"],
inplace=False,
)
[31]:
border_distance_negative.head()
[31]:
| cell_id | distance_to_cell_membrane_184_genes | cell_area | distance_to_cell_membrane_norm_184_genes | distance_to_cell_membrane_inverse_184_genes | |
|---|---|---|---|---|---|
| 0 | aelegcjd-1 | 3.260870 | 258.884963 | 0.202666 | 0.553775 |
| 1 | aeldpbbo-1 | 2.978403 | 176.880632 | 0.223946 | 0.579440 |
| 2 | hjbdpmpc-1 | 1.811994 | 262.673512 | 0.111802 | 0.742885 |
| 3 | hjbcgooh-1 | 1.888553 | 102.683823 | 0.186371 | 0.727671 |
| 4 | aeldbffd-1 | 2.138288 | 135.493824 | 0.183699 | 0.683859 |
[32]:
border_distance_positive.head()
[32]:
| cell_id | distance_to_cell_membrane_206_genes | cell_area | distance_to_cell_membrane_norm_206_genes | distance_to_cell_membrane_inverse_206_genes | |
|---|---|---|---|---|---|
| 0 | aelggapo-1 | 2.041371 | 253.712191 | 0.128160 | 0.699905 |
| 1 | hjbeaond-1 | 0.614755 | 46.964886 | 0.089705 | 1.275406 |
| 2 | aelgkmmk-1 | 1.364592 | 201.466363 | 0.096139 | 0.856049 |
| 3 | aelgfgmk-1 | 1.941890 | 222.395076 | 0.130215 | 0.717608 |
| 4 | hjbdlfgm-1 | 1.396414 | 92.053023 | 0.145544 | 0.846238 |
Session Info#
[33]:
print(sd.__version__) # spatialdata
print(spatialdata_plot.__version__)
0.7.2
0.2.13