Add function for calculating niches - #831
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LLehner
marked this pull request as draft
May 27, 2024 16:24
…into niche_definitions
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…into niche_definitions
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This was referenced Jun 12, 2024
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for more information, see https://pre-commit.ci
LLehner
commented
Mar 13, 2025
| inplace, | ||
| ) | ||
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| if resolutions is None: |
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Why not set this as default right away?
| if resolutions is None: | ||
| resolutions = [0.5] | ||
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| if distance is None: |
| elif libraries is not None and len(libraries) > 0: | ||
| return [f"{base_column}_{lib}" for lib in libraries] | ||
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| # For neighborhood and utag, we need to handle resolutions |
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Would do this with if-else block maybe
| groups: str | None, | ||
| n_neighbors: int | None, | ||
| resolutions: float | list[float], | ||
| subset_groups: list[str] | None, |
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why remove this completely? It serves a different purpose than masking. This was also described in the original tutorial. E.g. a mask allows to restrict niche calculation to specific cell types but they can have neighbors outside the masked region. Subsetting means only observations within that subset are considered as neighbors.
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| def _get_utag_niches( | ||
| adata: AnnData, | ||
| subset_groups: list[str] | None, |
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Here subsetting serves the same purpose as before.
| if library_key not in data.tables[table_key].obs.columns: | ||
| raise ValueError(f"'library_key' must be a column in 'adata.obs', got {library_key}") | ||
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| if n_neighbors is not None and not isinstance(n_neighbors, int): |
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Why check these separately?
| for param_name in param_specs["unused"]: | ||
| param_value = param_dict.get(param_name) | ||
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| # Special handling for boolean parameters with default values |
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Description
Adds a function that calculates niches using different strategies. The initial function calculates niches based on neighborhood profiles similar to here.
This PR will get updated with methods discussed in #789.