sc.tl.paga_expression_entropies(adata)
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- Python
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Description
I calculated sc.tl.paga(adata, groups='cell_ontology_class') without problems but I couldn't run sc.tl.paga_expression_entropies(adata).
I've modified the original code and it now runs - if this looks good you can perhaps update the original code? also, if it doesn't let me know so I don't carry over the mistakes!
from scipy.stats import entropy
groups_order, groups_masks = sc.utils.select_groups(tiss, key=tiss.uns['paga']['groups'])
entropies = []
for mask in groups_masks:
X_mask = tiss.X[mask].todense()
x_median = np.nanmedian(X_mask, axis=1,overwrite_input=True)
x_probs = (x_median - np.nanmin(x_median)) / (np.nanmax(x_median) - np.nanmin(x_median))
entropies.append(entropy(x_probs))
entropies
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Research direction
Start at the sc.tl.paga_expression_entropies(adata) entry point and reproduce the failure after running sc.tl.paga with the cell_ontology_class groups. Compare the existing behavior with the reported modification and establish a documented, working entropy result for grouped data.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, python
- Domain
- bioinformatics
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100