|
24 | 24 | "pancreas",
|
25 | 25 | "bonemarrow",
|
26 | 26 | "pbmc68k",
|
| 27 | + "larry_mono_clone_trajectory", |
| 28 | + "larry_neu_clone_trajectory", |
| 29 | + "larry_multilineage_clone_trajectory", |
27 | 30 | ]
|
28 | 31 |
|
29 | 32 |
|
@@ -301,6 +304,77 @@ def larry_multilineage(
|
301 | 304 | return adata
|
302 | 305 |
|
303 | 306 |
|
| 307 | +@beartype |
| 308 | +def larry_mono_clone_trajectory( |
| 309 | + file_path: str | Path = "data/external/larry_mono_clone_trajectory.h5ad", |
| 310 | +) -> anndata._core.anndata.AnnData: |
| 311 | + """ |
| 312 | + Pre-computed clone trajectory data for the LARRY monocyte lineage. |
| 313 | +
|
| 314 | + This contains the output of get_clone_trajectory applied to the larry_mono dataset. |
| 315 | + The clone trajectory information is used for visualizing clonal progression |
| 316 | + and calculating trajectory alignment with velocity predictions. |
| 317 | +
|
| 318 | + Returns: |
| 319 | + AnnData object with clone trajectory information |
| 320 | + """ |
| 321 | + url = "https://storage.googleapis.com/pyrovelocity/data/larry_mono_clone_trajectory.h5ad" |
| 322 | + adata = sc.read(file_path, backup_url=url, sparse=True, cache=True) |
| 323 | + expected_hash = ( |
| 324 | + "7bd6e4e9e9f7a830aeab2b342990cfedcf30eb0da5c5bfac4a76b8c7a4ab9142" |
| 325 | + ) |
| 326 | + _check_hash(file_path, expected_hash) |
| 327 | + return adata |
| 328 | + |
| 329 | + |
| 330 | +@beartype |
| 331 | +def larry_neu_clone_trajectory( |
| 332 | + file_path: str | Path = "data/external/larry_neu_clone_trajectory.h5ad", |
| 333 | +) -> anndata._core.anndata.AnnData: |
| 334 | + """ |
| 335 | + Pre-computed clone trajectory data for the LARRY neutrophil lineage. |
| 336 | +
|
| 337 | + This contains the output of get_clone_trajectory applied to the larry_neu dataset. |
| 338 | + The clone trajectory information is used for visualizing clonal progression |
| 339 | + and calculating trajectory alignment with velocity predictions. |
| 340 | +
|
| 341 | + Returns: |
| 342 | + AnnData object with clone trajectory information |
| 343 | + """ |
| 344 | + url = "https://storage.googleapis.com/pyrovelocity/data/larry_neu_clone_trajectory.h5ad" |
| 345 | + adata = sc.read(file_path, backup_url=url, sparse=True, cache=True) |
| 346 | + expected_hash = ( |
| 347 | + "f2e48b7ec1ed99ba6355e74afaaac8e9e97f9c0cad12dd0f09a0afb53c1c5d0a" |
| 348 | + ) |
| 349 | + _check_hash(file_path, expected_hash) |
| 350 | + return adata |
| 351 | + |
| 352 | + |
| 353 | +@beartype |
| 354 | +def larry_multilineage_clone_trajectory( |
| 355 | + file_path: str |
| 356 | + | Path = "data/external/larry_multilineage_clone_trajectory.h5ad", |
| 357 | +) -> anndata._core.anndata.AnnData: |
| 358 | + """ |
| 359 | + Pre-computed clone trajectory data for the LARRY multilineage dataset. |
| 360 | +
|
| 361 | + This contains the concatenated output of get_clone_trajectory applied to |
| 362 | + both larry_mono and larry_neu datasets. Using this pre-computed trajectory |
| 363 | + ensures consistent fate analysis across both lineages without recomputing |
| 364 | + trajectories separately. |
| 365 | +
|
| 366 | + Returns: |
| 367 | + AnnData object with clone trajectory information |
| 368 | + """ |
| 369 | + url = "https://storage.googleapis.com/pyrovelocity/data/larry_multilineage_clone_trajectory.h5ad" |
| 370 | + adata = sc.read(file_path, backup_url=url, sparse=True, cache=True) |
| 371 | + expected_hash = ( |
| 372 | + "d5c99fd45ab7f17c4a78cb7dc58c6bd3a3dd3ade89d10a8d8adf1b7be0a84cc7" |
| 373 | + ) |
| 374 | + _check_hash(file_path, expected_hash) |
| 375 | + return adata |
| 376 | + |
| 377 | + |
304 | 378 | @beartype
|
305 | 379 | def pancreas(
|
306 | 380 | file_path: str | Path = "data/external/pancreas.h5ad",
|
|
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