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Visium hd #211
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Visium hd #211
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #211 +/- ##
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+ Coverage 35.91% 44.83% +8.91%
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Files 19 22 +3
Lines 1715 2186 +471
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+ Hits 616 980 +364
- Misses 1099 1206 +107
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Thanks for the PR, it looks great, very curios to experiment with it! I have some tasks on my todo list but I hope to get to this soon. |
Hi, great PR, it looks very interesting! I´m trying to use it for my project, but ran into an error. I´m relatively new to using PRs on github, so maybe I already did a mistake during setup. from spatialdata_io import visium_hd FileNotFoundError: [Errno 2] Unable to synchronously open file (unable to open file: name = '/files/03-SpaceRanger-Results/P31904_402/outs/P31904_402_feature_slice.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0) "P31904_402_feature_slice.h5" indeed does not exist, it should simply be "feature_slice.h5" in "outs" of the "P31904_402" folder. I don´t understand why the error is thrown though, since that part of the code was not changed to my understanding? Here is the full traceback: File ~/anaconda3/envs/sd_pr_test/lib/python3.12/site-packages/spatialdata_io/readers/visium_hd.py:115, in visium_hd(path, dataset_id, filtered_counts_file, bin_size, bins_as_squares, annotate_table_by_labels, fullres_image_file, load_all_images, imread_kwargs, image_models_kwargs, anndata_kwargs) File ~/anaconda3/envs/sd_pr_test/lib/python3.12/site-packages/spatialdata_io/readers/visium_hd.py:471, in _parse_metadata(path, filename_prefix) File ~/anaconda3/envs/sd_pr_test/lib/python3.12/site-packages/h5py/_hl/files.py:562, in File.init(self, name, mode, driver, libver, userblock_size, swmr, rdcc_nslots, rdcc_nbytes, rdcc_w0, track_order, fs_strategy, fs_persist, fs_threshold, fs_page_size, page_buf_size, min_meta_keep, min_raw_keep, locking, alignment_threshold, alignment_interval, meta_block_size, **kwds) File ~/anaconda3/envs/sd_pr_test/lib/python3.12/site-packages/h5py/_hl/files.py:235, in make_fid(name, mode, userblock_size, fapl, fcpl, swmr) File h5py/_objects.pyx:54, in h5py._objects.with_phil.wrapper() File h5py/_objects.pyx:55, in h5py._objects.with_phil.wrapper() File h5py/h5f.pyx:102, in h5py.h5f.open() |
Hi @t-a-m-i , Does this work using spatialdata-io (last release), installed via pip install spatialdata-io? And then do:
I don't think the error you encounter is related to this PR. |
yes, I was also confused about the error since it didn´t seem related to the PR. I didn´t realise though that there was a new release. I get the same error with the latest version of spatialdata-io (v0.1.5), with v0.1.4 everything works fine, I´ll do a bug report then, thanks! |
Notebook relevant for the PR review: https://scverse.zulipchat.com/#narrow/channel/315824-spatial/topic/SpatialData/near/479568220 |
This adds support for annotating the resulting tables with corresponding labels layers (the bins).
Annotating the table by a labels layer has the advantage that the bins, and their expression levels can be viewed in napari-spatialdata, which is not possible if you annotate via the shapes layers ( it is possible when setting
bins_as_squares
toFalse
, but this will give you circles, not squares, which is not ideal ).Viewing and loading expression levels for 016um and 008um bins is quite fast, viewing the 002um bins is also still possible, althoug loading expression levels associated with the bins takes some seconds for each gene, but once loaded is quite fast and convenient to view.
See screenshot for 008um:
It is not as snappy as https://github.com/scverse/spatialdata/blob/8879aff17b8169c6bb6ff3537e4ddcee0204f168/src/spatialdata/_core/operations/rasterize_bins.py#L28, but maybe a little bit more convenient in use.
If this PR would be merged, then this function
spatialdata.rasterize_bins
would also need to be updated. I would remove thebins
parameter, and estimate the transformation only using the tables, i.e. usingtable.obsm[ 'spatial' ]
and thecol_key
androw_key
intable.obs
; or get the transformation from the labels layer.