pseudotimespace_global() always yields "Connectivity is undefined for the null graph" exception

[marcouderzo]

Hello,
I have a strange issue with running st.spatial.trajectory.pseudotimespace_global() on one particular dataset, which is a spatial subset of a full Visium HD sample. This is my code:

adata_gd75 = ad.read_h5ad("analysis_output/adata_subset.h5ad")
adata_gd75 = st.convert_scanpy(adata_gd75)

adata_gd75.obs['clusters'].value_counts()

clusters
7 490
16 383
6 325
14 271
22 269
0 260
4 249
15 241
10 226
2 224
21 215
8 212
5 176
1 169
17 153
20 111
12 100
9 82
13 74
23 63
27 48
3 42
29 38
28 35
11 28
19 23
25 18
30 7
24 7
32 7
18 5


sc.pp.pca(adata_gd75, n_comps=30, random_state=30)
sc.pp.neighbors(adata_gd75, n_neighbors=15, use_rep="X_pca")
sc.tl.umap(adata_gd75, random_state=30)
sc.pl.umap(adata_gd75, color="clusters")

adata_gd75.uns["iroot"] = st.spatial.trajectory.set_root(adata_gd75,use_label="clusters",cluster=21,use_raw=False)
st.spatial.trajectory.pseudotime(adata_gd75,eps=50,use_rep="X_pca",use_label="clusters") # runs indefinitely

At first, the pseudotime() call never finished running, and kept one of my CPU cores at 100% for three days straight. By analyzing the call stack, it kept recursing around those nx calls:

networkx/algorithms/simple_paths.py: all_simple_paths(...)
networkx/algorithms/simple_paths.py: all_simple_edge_paths(...)
networkx/algorithms/simple_paths.py: _all_simple_edge_paths(...)

The same code, on a subset of another sample, worked just fine and finished the computation in less than an hour. I then found out that by taking a wider subset of the adata_gd75 subset, the call finished running and returned some trajectories. Maybe it wasn't finding any trajectories at all?

However, afterwards, I run:

for lin in lineage:
 lin = [str(c) for c in lin]
 lineage_str = array_to_string(lin)
 try:
 st.spatial.trajectory.pseudotimespace_global(adata_gd75,use_label="clusters", list_clusters=lin)
 st.pl.cluster_plot(adata_gd75,use_label="clusters", 
 list_clusters=lin, 
 show_trajectories=True,
 show_subcluster=True, 
 figsize = [12,12], 
 cmap='cet_glasbey',
 fname = f"./figures/all_samples/lineage_tracing/GD7.5_niches_subset/GD75_{lineage_str}_pseudotimespace_global.png")
 except Exception as e:
 print(f'{lineage_str}:{e}')

This yields:

...

Start to construct the trajectory: 28 -> 17 -> 15
28-17-15:Connectivity is undefined for the null graph.
Start to construct the trajectory: 28 -> 16 -> 1
28-1-16:Connectivity is undefined for the null graph.
Start to construct the trajectory: 2 -> 28 -> 16
28-2-16:Connectivity is undefined for the null graph.
Start to construct the trajectory: 28 -> 4 -> 16
28-4-16:Connectivity is undefined for the null graph.
Start to construct the trajectory: 28 -> 16 -> 7
28-7-16:too many indices for array: array is 1-dimensional, but 2 were indexed
Start to construct the trajectory: 28 -> 12 -> 16
28-12-16:Connectivity is undefined for the null graph.
Start to construct the trajectory: 28 -> 16 -> 15
28-15-16:Connectivity is undefined for the null graph.

...

So I'm going to ask: in stLearn, what causes it to yield this "Connectivity is undefined for the null graph." exception?

Any advice? Thanks.

Best,
Marco Uderzo